{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "#color = sns.color_palette()\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.344167</td>\n",
       "      <td>0.363625</td>\n",
       "      <td>0.805833</td>\n",
       "      <td>0.160446</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.363478</td>\n",
       "      <td>0.353739</td>\n",
       "      <td>0.696087</td>\n",
       "      <td>0.248539</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.196364</td>\n",
       "      <td>0.189405</td>\n",
       "      <td>0.437273</td>\n",
       "      <td>0.248309</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2011-01-04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.212122</td>\n",
       "      <td>0.590435</td>\n",
       "      <td>0.160296</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.226957</td>\n",
       "      <td>0.229270</td>\n",
       "      <td>0.436957</td>\n",
       "      <td>0.186900</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant      dteday  season  yr  mnth  holiday  weekday  workingday  \\\n",
       "0        1  2011-01-01       1   0     1        0        6           0   \n",
       "1        2  2011-01-02       1   0     1        0        0           0   \n",
       "2        3  2011-01-03       1   0     1        0        1           1   \n",
       "3        4  2011-01-04       1   0     1        0        2           1   \n",
       "4        5  2011-01-05       1   0     1        0        3           1   \n",
       "\n",
       "   weathersit      temp     atemp       hum  windspeed  casual  registered  \\\n",
       "0           2  0.344167  0.363625  0.805833   0.160446     331         654   \n",
       "1           2  0.363478  0.353739  0.696087   0.248539     131         670   \n",
       "2           1  0.196364  0.189405  0.437273   0.248309     120        1229   \n",
       "3           1  0.200000  0.212122  0.590435   0.160296     108        1454   \n",
       "4           1  0.226957  0.229270  0.436957   0.186900      82        1518   \n",
       "\n",
       "    cnt  \n",
       "0   985  \n",
       "1   801  \n",
       "2  1349  \n",
       "3  1562  \n",
       "4  1600  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# path to where the data lies\n",
    "#dpath = './data/'\n",
    "data = pd.read_csv(\"day.csv\")\n",
    "\n",
    "#通过观察前5行，了解数据每列（特征）的概况\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 731 entries, 0 to 730\n",
      "Data columns (total 16 columns):\n",
      "instant       731 non-null int64\n",
      "dteday        731 non-null object\n",
      "season        731 non-null int64\n",
      "yr            731 non-null int64\n",
      "mnth          731 non-null int64\n",
      "holiday       731 non-null int64\n",
      "weekday       731 non-null int64\n",
      "workingday    731 non-null int64\n",
      "weathersit    731 non-null int64\n",
      "temp          731 non-null float64\n",
      "atemp         731 non-null float64\n",
      "hum           731 non-null float64\n",
      "windspeed     731 non-null float64\n",
      "casual        731 non-null int64\n",
      "registered    731 non-null int64\n",
      "cnt           731 non-null int64\n",
      "dtypes: float64(4), int64(11), object(1)\n",
      "memory usage: 91.4+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>2.496580</td>\n",
       "      <td>0.500684</td>\n",
       "      <td>6.519836</td>\n",
       "      <td>0.028728</td>\n",
       "      <td>2.997264</td>\n",
       "      <td>0.683995</td>\n",
       "      <td>1.395349</td>\n",
       "      <td>0.495385</td>\n",
       "      <td>0.474354</td>\n",
       "      <td>0.627894</td>\n",
       "      <td>0.190486</td>\n",
       "      <td>848.176471</td>\n",
       "      <td>3656.172367</td>\n",
       "      <td>4504.348837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>211.165812</td>\n",
       "      <td>1.110807</td>\n",
       "      <td>0.500342</td>\n",
       "      <td>3.451913</td>\n",
       "      <td>0.167155</td>\n",
       "      <td>2.004787</td>\n",
       "      <td>0.465233</td>\n",
       "      <td>0.544894</td>\n",
       "      <td>0.183051</td>\n",
       "      <td>0.162961</td>\n",
       "      <td>0.142429</td>\n",
       "      <td>0.077498</td>\n",
       "      <td>686.622488</td>\n",
       "      <td>1560.256377</td>\n",
       "      <td>1937.211452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059130</td>\n",
       "      <td>0.079070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022392</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>183.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.337083</td>\n",
       "      <td>0.337842</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.134950</td>\n",
       "      <td>315.500000</td>\n",
       "      <td>2497.000000</td>\n",
       "      <td>3152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.498333</td>\n",
       "      <td>0.486733</td>\n",
       "      <td>0.626667</td>\n",
       "      <td>0.180975</td>\n",
       "      <td>713.000000</td>\n",
       "      <td>3662.000000</td>\n",
       "      <td>4548.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>548.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.655417</td>\n",
       "      <td>0.608602</td>\n",
       "      <td>0.730209</td>\n",
       "      <td>0.233214</td>\n",
       "      <td>1096.000000</td>\n",
       "      <td>4776.500000</td>\n",
       "      <td>5956.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.861667</td>\n",
       "      <td>0.840896</td>\n",
       "      <td>0.972500</td>\n",
       "      <td>0.507463</td>\n",
       "      <td>3410.000000</td>\n",
       "      <td>6946.000000</td>\n",
       "      <td>8714.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant      season          yr        mnth     holiday     weekday  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean   366.000000    2.496580    0.500684    6.519836    0.028728    2.997264   \n",
       "std    211.165812    1.110807    0.500342    3.451913    0.167155    2.004787   \n",
       "min      1.000000    1.000000    0.000000    1.000000    0.000000    0.000000   \n",
       "25%    183.500000    2.000000    0.000000    4.000000    0.000000    1.000000   \n",
       "50%    366.000000    3.000000    1.000000    7.000000    0.000000    3.000000   \n",
       "75%    548.500000    3.000000    1.000000   10.000000    0.000000    5.000000   \n",
       "max    731.000000    4.000000    1.000000   12.000000    1.000000    6.000000   \n",
       "\n",
       "       workingday  weathersit        temp       atemp         hum   windspeed  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean     0.683995    1.395349    0.495385    0.474354    0.627894    0.190486   \n",
       "std      0.465233    0.544894    0.183051    0.162961    0.142429    0.077498   \n",
       "min      0.000000    1.000000    0.059130    0.079070    0.000000    0.022392   \n",
       "25%      0.000000    1.000000    0.337083    0.337842    0.520000    0.134950   \n",
       "50%      1.000000    1.000000    0.498333    0.486733    0.626667    0.180975   \n",
       "75%      1.000000    2.000000    0.655417    0.608602    0.730209    0.233214   \n",
       "max      1.000000    3.000000    0.861667    0.840896    0.972500    0.507463   \n",
       "\n",
       "            casual   registered          cnt  \n",
       "count   731.000000   731.000000   731.000000  \n",
       "mean    848.176471  3656.172367  4504.348837  \n",
       "std     686.622488  1560.256377  1937.211452  \n",
       "min       2.000000    20.000000    22.000000  \n",
       "25%     315.500000  2497.000000  3152.000000  \n",
       "50%     713.000000  3662.000000  4548.000000  \n",
       "75%    1096.000000  4776.500000  5956.000000  \n",
       "max    3410.000000  6946.000000  8714.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 各属性的统计特性\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1zfxzyyGnw1FBShOIUkBzWycbymuZmZMcMnee9+WCqRkUZCTw0Mq96AWNKhCaQJQC1u+rob3TsGBCqtOhDBuXS7jtvInsPNzAa1sPOx2OCkLh8VNLDStvY0t1u37e+GGMxD+dXYaPSqrJTY0jKznW6XCG1eUzx/HQyr38+vVdfGH6GCLc+ptS+U8/LSrsbTlwjGPH2zm7IPyGvnG7hB8tnEpJVRPLi/SKLNU/mkBUWDPG8P7uKjISo0P+0l1fLpyWQWHuaH771m6a2/S+EOU/TSAqrK3cVcnh+hbOLkgP+Ut3fRER7rx4KkcbWnn0gxKnw1FBRPtAVFh76L29JMVGckpOktOhOOq0vBQuPSWTB94tZvHMLPLTBm8U4t76xGBk9osp/2gLRIWtNSXVrC2t4YxJaUS49L/Czy+bTrTbxT0vbdHLepVf9H+NCkvGGH79xi4yEqOZG8LjXvVHxqgYfnzxVFYVV/P3DQecDkcFAU0gKiy9t7uSdWW1fO+CAqIi9L9Btxvmjmf2+GR+8cp2DhxrdjocNcLp/xwVdrpbHzkpsVxTmNP3BmHE5RJ+8+VZdHQabnv2E9o6dJws5ZsmEBV2Xtt6mK0H6vn3Cydr68OL/LR4/veqU9hUfoz/enWH0+GoEUz/96iwcrytg1/9cwdTxyayZNY4p8MZsS4+OZNbzsznyY/KeHbNPqfDUSOUXsarwsof3inmwLFmnv/2Atyu8Lzvw193XTyVkspGfvL3rUS5XVytp/tUD9oCUWGj+GgDj31QwlVzsjlNr7zqU6TbxUNfmcNZBWn8+G+bWV5U7nRIaoTRFogaVk7dVNbVZbjnpa3ERrq56+KpQ/IawaC/A13GRLp55KuFfOPpdfz4hc28UFTBpadkEtlj0EW9GTA8aQtEhYWH39/L6pIafnLpNNISop0OJ6jERrl56mtzObsgjbVlNTz83l5KKhudDkuNANoCUSFv/b5afvPGbi49JZMv63n8gES4XSw6KZPc1Hj+sfEAj31YyqT0BOZPSGVSRoLT4SmHaAJRIe3Y8TbueG4DmUkx/PcXT0bCdMDEwTItcxSTMhJYU1rDe7uO8pc1+4h0C2/vPMLE9ATyUuNIiIkkOsJFlzG0dnSxuqSajs4uOroMgjWEfEykm7SEaNIStTUYzDSBqJDV1NrB155cR2VDK8u+NZ9RMZFOhxQSIt0uzpyUxoIJqZRWNbHtYB3VjW2s31fO8QCGg391yyEuOyWTK04dp6cXg4wmEBWSWjs6ufWZIjZX1PHg9bM5dfxop0MKOW6XMCkjgUkZCVw/bzzGGKqb2mhu66SlvRMRISbSxT83HyLS7SLCJRisGSCbWjuoamzjYF0zB481c+8/d/C7t/bwbxcWcNPpeZ/rpFcjkyYQFXLqjrfzvaUbWFVczW+unsmik8Y6HVJYEBGvLYjEHi2/SLd1dVdqgjWJ1/XzxrP7SAP/9eoO7v3nDp4vquCxmwrJSYkbrtBVgDTNq5Cy/WA9ix/4kI/3VnHfl07mS3OynQ5J+WHymESeuPk0Hr2xkMP1LVz5x4/YeqDO6bBUHzSBqJBQ29TGr/65nSv+uIrWjk6WfWsB15ym9yYEExHhoulj+Nt3FhAd4eKaP31MaVWT02GpXugpLBW0Wjs6WV1SwxvbDrNi40Ga2jr44uxs7lw0lXS9uidoTcpI5MXbTue6R1fz7Jp9fPfcSYyOj3I6LOWFJhA1YjS1drC6pJr9Ncc5Wt9Ca0cXrR1dtHV00drR+enzptYO9lcfZ3/NcTq6DHFRbi6YNobvnT+JyWMSnd4NNQjGjIrhsRsLueT3H/CXNfv41tkTdeTkEUgTiHJUQ0s768pq2HW4gYraZjwnUnUJREe4iYpwER3h+vTf2Cg3UzMTWXTSWGaPH82ZBWnERLod2wc1NCakJ3DtaeN56qMyXtxQwbV6SnLE0QSiHNHQ0s77uytZU1pDZ5che3Qs50/L4KYFeeSmxjE2KYYot0tv/Atzk8ckcsG0DN7acZSZ2fVMyxzldEjKgyYQNex2HW7g+fXltLR3MitnNOdNSSfVvvyzoraZilrvU6nqgH3h6ZzJGWw5UMeKTQeZkB5PdIS2NkcKPamohk2XMfxr6yGe+riMUTGRfO/8Aq6ak/1p8lDKG7dLuHLWOOqa23lr+xGnw1EetAWihkWXMby04QBF+2o5LS+Fy7wMCa6UL+NT45mbn8JHe6uZnTuazKRYp0NSaAtEDQPP5HHelHSumJWlyUP128LpY4mOdPGmtkJGDL9aICKyCPgd4AYeM8b8T4/10cDTwBygGrjGGFNmr7sbuAXoBO4wxrzeW50icjvwfWAikG6MqbKXi13+EuA4cLMx5pOA91wNmze2Hfk0eVw4bUzAHeP9nQxJ9U9fk30N1bb+io1yc1ZBOm9uP0J5zXFyUuL0M+GwPn8GiogbeBC4GJgOXCci03sUuwWoNcZMAu4H7rO3nQ5cC8wAFgF/FBF3H3WuAi4E9vV4jYuBAvvvVuCh/u2qcsLWA3W8v6eSuXkpA0oeSgGcPiGVuCg3b+3QVshI4M95hLlAsTGmxBjTBiwFlvQoswR4yn78AnCB3WJYAiw1xrQaY0qBYrs+n3UaYzZ0t168vMbTxrIaSBaRzP7srBpeRxtaeOGTCnJGx3LZKZmaPNSARUe6OWdyOnuONuowJyOAPwlkHFDu8bzCXua1jDGmA6gDUnvZ1p86A4kDEblVRIpEpKiysrKPKtVQ6ejs4rm1+4l0CdfPyyVC+zzUIJmXn0pCdAQrdx11OpSw508fiLefjcbPMr6We/s26VlnIHFgjHkEeASgsLCwrzrVEFm5u5Ij9a3ctCCXpNihn8ipr3Pwej48dERFuFgwMZU3tx/hSH0LY0bFOB1S2PLnZ2EF4DmRdDZw0FcZEYkAkoCaXrb1p85A4lAjwOG6Ft7bVcmsnGSmjNU7h9Xgm5uXQoRL+GhvtdOhhDV/Esg6oEBE8kUkCqtTfEWPMiuAm+zHVwHvGGOMvfxaEYkWkXysDvC1ftbZ0wrgRrHMB+qMMYf8iF8No84uw4sbKoiOdHHpydpFpYZGfHQEp45PZsP+WppaO5wOJ2z1mUDsPo3bgdeBHcByY8w2EfmFiFxuF3scSBWRYuAHwF32ttuA5cB24F/Ad40xnb7qBBCRO0SkAquFsVlEHrNf41WgBKsj/lHgtgHvvRp0S9ftp6K2mcWnZBEfrfepqqFz+sQ0OroM68pqnA4lbInVUAhNhYWFpqioyOkwwkZDSzvn/XolCdERfPOsCXrVlfJLb/1TffVtPbGqlMP1Lfx44VTcrhM/b9rvFTgRWW+MKeyrnF4aowbNw+/tpaqxjUtO1kt21fBYMCGVhpYOdh2udzqUsKQJRA2Kg8eaeeyDUpbMyiJ7dJzT4agwUTAmkVExEawrq3U6lLCkCUQNit+8sRsD/GjhFKdDUWHE7RJm545m95EG6prbnQ4n7GgCUQNWVtXESxsP8NX5udr6UMOuMDcFA6zfp62Q4aaXyagBe+DdYiJcwrfOmeB0KCoIDXQgxpT4KCamx7N+Xw3nTknHpf1vw0ZbIGpA9lU38fcNB7hhXi4ZiXpHsHJGYV4Ktcfb2VvZ6HQoYUUTiBqQB96xWh/f1taHctD0zFHERLrYsP+Y06GEFU0gKmAVtcd5ccMBrps7ngwdj0g5KNLt4uRxyWw7WEdrR6fT4YQN7QNRXvkzOOGfPyxDgFvP1taHct6snGTWldWw41A9s3JGOx1OWNAWiApI3fF2lq7bz+KZWWQl6/zUynm5qXEkx0WysVxPYw0XTSAqIH9Zs4/jbZ188yxtfaiRwSXCrJxk9hxppKFF7wkZDppAVL91dHbx5EdlnFWQxvQsHa5djRyzspMxwOaKOqdDCQuaQFS/bSw/RmVDK986e6LToSh1goxRMYxLjtXTWMNEE4jqF2MMH+2tZurYRM6YlOp0OEp9zszsJA4ca6ZM50wfcppAVL+UVjdxuL6Fr52RpyPuqhHp5OxkAF7ZrBOWDjVNIKpfPt5bTWykmyWzxjkdilJeJcVGkpcax8ubdMLSoaYJRPmttqmN7QfrmZufQkyk2+lwlPLp5Oxkdh1pYNfhBqdDCWmaQJTfVpdWIwLz8lOcDkWpXp2UNQqX6GmsoaYJRPmlvbOLorJapmeOIjkuyulwlOpVYkwkp09M4+VNBwnlabudpglE+WVzRR3N7Z3Mn6BXXqngsHhmJmXVx9l6QKe7HSo6Fpbyy5rSatITo8lPiwcGPoeDUkNt4Yyx3PPSVl7efJCTs5OcDickaQtE9elAbTMVtc3My0/RS3dV0EiOi+LsgnRe2XSQri49jTUUNIGoPq0prSbSLZyqI5yqIHPZzEwO1rXwyX6d7nYoaAJRvWpu62RTxTFmZicTG6WX7qrgcuG0MURHuHhls94TMhQ0gahebSivpb3TME87z1UQSoyJ5PypGbyy+RCdehpr0GkCUT4ZY1hTUkPO6FjG6ZwfKkgtnplFVWMra0qqnQ4l5GgCUT6VVDVR2djKvHxtfajgdd6UDOKj3LysNxUOOk0gyqc1Jda4V3oJpApmsVFuLpo+hte2Hqato8vpcEKKJhDlVX1LO9sP1TMndzSRbv2YqOC2eGYWx463s6q4yulQQop+Myivispq6DIwV8e9UiHgrIJ0RsVE8PImPY01mDSBqM/p6OxibWkNBRkJpCVEOx2OUgMWFeFi0UljeWP7EVraO50OJ2RoAlGf8/bOo9S3dOiouyqkLJ6ZRWNrByt3HXU6lJChCUR9zl9W7yMpNpIpY0c5HYpSg2bBhFRS46N4WW8qHDSaQNQJSqua+GBPFafljcbt0nGvVOiIcLu45ORM3t5xhKbWDqfDCQmaQNQJ/rpmHxEuoTBPT1+p0LN4ZhYt7V28teOI06GEBL8SiIgsEpFdIlIsInd5WR8tIsvs9WtEJM9j3d328l0isrCvOkUk365jj11nlL38ZhGpFJGN9t83BrLj6vNa2jt5fn0FC2eMZVRMpNPhKDXoCnNHM3ZUjM6XPkj6TCAi4gYeBC4GpgPXicj0HsVuAWqNMZOA+4H77G2nA9cCM4BFwB9FxN1HnfcB9xtjCoBau+5uy4wxs+y/xwLaY+XTPzYe4Njxdr4yP9fpUJQaEi6XcOkpmby3+yh1x9udDifo+dMCmQsUG2NKjDFtwFJgSY8yS4Cn7McvABeINXHEEmCpMabVGFMKFNv1ea3T3uZ8uw7sOq8IfPeUv4wxPLGqjKljE5k/QU9fqdC1eGYW7Z2G17cfdjqUoOdPAhkHlHs8r7CXeS1jjOkA6oDUXrb1tTwVOGbX4e21viQim0XkBRHJ8SN25ac1pTXsPNzA187I00mjVEibmZ1ETkqs3lQ4CPxJIN6+TXqOi+yrzGAtB3gZyDPGnAK8xWctnhMDEblVRIpEpKiystJbEeXFk6vKSI6LZMmsnr8NlAotIsLiU7L4aG81VY2tTocT1PxJIBWA56/9bKBn6v60jIhEAElATS/b+lpeBSTbdZzwWsaYamNM99F+FJjjLVhjzCPGmEJjTGF6erofu6cqao/zxvbDXDd3PDGROmmUCn2LZ2bR2WV4dYt2pg+EPwlkHVBgXx0VhdUpvqJHmRXATfbjq4B3jDHGXn6tfZVWPlAArPVVp73Nu3Yd2HX+A0BEMj1e73JgR/92VfnyzOp9iIh2nquwMXVsIlPHJvK39RVOhxLU+kwgdn/E7cDrWF/ay40x20TkFyJyuV3scSBVRIqBHwB32dtuA5YD24F/Ad81xnT6qtOu607gB3ZdqXbdAHeIyDYR2QTcAdw8sF1XYE1Zu3RtOV+YPkYnjVJhQ0S4ak42myrq2H2kwelwgpZYP/pDU2FhoSkqKnI6jBHtubX7ufvFLSy7df4J09b+dc1+B6NSauCunze+1/VVja3M/6+3ueXMfO6+ZNowRRUcRGS9Maawr3J6J3oYM8bw5KoypmWO0mHbVdhJS4jm3CkZvLjhAB2dOtFUIDSBhLGPS6rZdaSBr52ul+6q8HTVnGwqG1r5YI9ONBWIiL6LqFB17ys7iIty09zeqaesVFg6f2oGo+MieX59OedNzXA6nKCjLZAwtbeykR1aEBtzAAAWb0lEQVSH6pmbl6JT1qqwFRXh4spTs3lz+xEqG/SekP7Sb44w9ej7JbhdwoKJqX0XViqEXT9vPO2dhuVF5X0XVifQBBKGjta38OInB5idO5pEHXVXhblJGQksmJDKc2v309kVulelDgXtAwlDj68qpaOri7MmpTkdilJDprd+vZ6X+N4wfzy3/3UD7++u1L6QftAWSJipb2nnr6v3c/HJmaQmRDsdjlIjwhemjyUtIZpn1+xzOpSgogkkzDy5qoyG1g6+c85Ep0NRasSIinBxzWnZvLPzKBW1x50OJ2hoAgkj9S3tPPZBCRdOG8NJ45KcDkepEeWGebmICE+uKnM6lKChfSBh5IkPy6hv6eD7FxY4HYpSjvLVP3JS1iieXr2P711QQFKsXmDSF22BhIm65nYe/1BbH0r15syCdNo6uli6Vm+s9YcmkDDxxKpSbX0o1YdxybFMSI/niVVltHXo+Fh90QQSBiobWnn0/RIWztDWh1J9OWtSOofrW3TKWz9oAgkDv3t7N60dXdy5aKrToSg14k0ek8DUsYk8uLJYR+ntgyaQELe3spHn1pZz/bzxTEhPcDocpUY8EeH7FxZQUtnEPzZqK6Q3mkBC3H2v7SQ20s0dF2jfh1L+WjhjLDOyRvG7t/fQrq0QnzSBhLAP9lTyxvYjfOfciaTpXedK+U1E+OEXJrO/5jgv6LzpPmkCCVEt7Z389KWt5KfF842z8p0OR6mgc96UDGblJPOHt/fQ0t7pdDgjkiaQEPWn90ooqz7OL5ecRHSE2+lwlAo6IsLdF0/lYF0LD7+31+lwRiRNICGorKqJB1cWs3hmFmcW6Ii7SgVq3oRUFs/M4qGVeymv0TGyetIEEmI6uww/fH4T0REufnrpNKfDUSro/eclU3G7hF++st3pUEYcTSAh5uH39rJ+Xy33XnESGaNinA5HqaCXmRTL7edP4o3tR3h351GnwxlRNIGEkK0H6rj/zd1cdkoml8/McjocpULGLWfmM3lMAnf+bTO1TW1OhzNiaAIJEfUt7dzx3AZSE6K494qTEBGnQ1IqZERHuLn/mlnUHm/jP/++BWN06lvQBBISuroM/750I/trjvP7a08lOS7K6ZCUCjkzspL4wUVTeG3rYV785IDT4YwImkBCwG/f3sPbO4/y08umM29CqtPhKBWybj17AnPzUrjnpa1sO1jndDiO0wmlgtyLn1Tw+7f3cPWcbG5ckPu59b4mzlFK9Z/bJTxww6kseWAV33yqiH/cfibpieE7yoO2QILYv7Ye4j+e38QZk1L5pfZ7KDUsMhJjePTGQmqOt/GtZ4rC+i51TSBB6t1dR/necxuYlZPMI18tJCZS7zZXaricNC6J+788iw3lx/jGU0U0t4VnEtEEEoSeLyrnm08VMXlMIk/cPJf4aD0TqdRwu/jkTH591UxW7a3ilqfWhWUS0W+eINLVZfjDO8Xc/9ZuzpyUxkNfmU1iTKTTYSkVcnrrO7x+3vhPH39pTjYi8MPnN3Hto6t55KtzGBNGN/BqCyRIVDa0cvOT67j/rd188dRx/Pnm0zR5KDUCfHF2Ng/dMIc9Rxq47A8fsn5frdMhDRtNICOcMYZXtxzi4t99wJqSan515Un85ssziYrQQ6fUSLHopLH8/bYziI108+U/fcz/vr4zLDrX9VtoBNt+sJ7rH13Dbc9+QnpiNCtuP5Mb5uXq1VZKjUBTxiby8u1ncuWp43jw3b1c8vsPeHvHkZC+a137QEYYYwxrSmv403t7eXdXJclxkfzyipO4fu543C5NHEqNZElxkfz66pksmZXFPS9t5ZanipiZncTt5xdw3pR0Ityh9ZvdrwQiIouA3wFu4DFjzP/0WB8NPA3MAaqBa4wxZfa6u4FbgE7gDmPM673VKSL5wFIgBfgE+Koxpq231wh2xhh2H2nkta2HeGnDAcqqj5MaH8UPL5rMjQvySIrz3dehNwoqNfKcVZDOWz84x77Rt5hvPl3EmFHRXDUnm0UzMjlp3KiQOJPQZwIRETfwIHARUAGsE5EVxhjPwfFvAWqNMZNE5FrgPuAaEZkOXAvMALKAt0Rksr2NrzrvA+43xiwVkYftuh/y9RoDfQOc0NTawZ6jjWyuOMbG/cdYtbeKI/WtiMCCCal897xJLJ6Zpfd2KBXEIt0urjltPF+cnc3bO46ybN1+Hlq5lwff3cuYUdGcMTGNU3NHMzM7ify0+KC8KMafFshcoNgYUwIgIkuBJYBnAlkC/B/78QvAA2Kl1yXAUmNMK1AqIsV2fXirU0R2AOcD19tlnrLrfcjXa5hhOMFojKHLWJM1dRmDMdBlDJ3G0N7RRXN7Jy3tnTS3WY+b2ztpbuukoaWdow2tVHr87a85zuH6lk/rTkuIYt6EVM4uSOOcyRmMTQqfSwCVCgeRbheLThrLopPGUt3Yyru7Knln5xHe31PFixs+G5QxLSGK3NR4clPjyEqKJTkukqTYSJLjokiOiyQ20k1UhIsot8v6t/vP7SLCJbhEEGFYWzb+JJBxQLnH8wpgnq8yxpgOEakDUu3lq3tsO85+7K3OVOCYMabDS3lfr1Hlxz70y2tbDnHH0g12whh4fYnREaSPiiY9IZrTJ6UyMT2BiekJnJKdRGZSTEg0ZZVSfUtNsE5jXTUnG2MM5TXNbDtYx76a45RVNVFW3cRHxdUcbWgJ+LtHBFwifOvsCfx40dTB3YEe/Ekg3r7deu6arzK+lnvrSeqtvL9xICK3ArfaTxtFZJeX7dIYgsTjkFDZl1DZD9B9GakGZV9uGIRABkGf+3Lnf8Odgdf/+ZFZvfAngVQAOR7Ps4GDPspUiEgEkATU9LGtt+VVQLKIRNitEM/yvl7jBMaYR4BHetshESkyxhT2ViZYhMq+hMp+gO7LSKX7Mvj8uaZsHVAgIvkiEoXVKb6iR5kVwE3246uAd+y+iRXAtSISbV9dVQCs9VWnvc27dh3Ydf6jj9dQSinlgD5bIHZ/w+3A61iX3P7ZGLNNRH4BFBljVgCPA8/YneQ1WAkBu9xyrA73DuC7xphOAG912i95J7BURO4FNth14+s1lFJKOUPC8Ue8iNxqn+oKeqGyL6GyH6D7MlLpvgxBHOGYQJRSSg1caN1Xr5RSatiEXAIRkf8VkZ0isllE/i4iyR7r7haRYhHZJSILPZYvspcVi8hdHsvzRWSNiOwRkWV2h/+I4CvmkUREckTkXRHZISLbROTf7OUpIvKm/b6+KSKj7eUiIr+392mziMz2qOsmu/weEbnJ12sO8f64RWSDiLxiP/f6+bAvGllm78caEcnzqMPrZ3CY9yNZRF6w/5/sEJEFQXxM/t3+bG0VkedEJCZYjouI/FlEjorIVo9lg3YcRGSOiGyxt/m9yBDccGaMCak/4AtAhP34PuA++/F0YBMQDeQDe7E68N324wlAlF1mur3NcuBa+/HDwHec3j87Fp8xj6Q/IBOYbT9OBHbbx+H/AnfZy+/yOEaXAK9h3fMzH1hjL08BSux/R9uPRzuwPz8A/gq80tvnA7gNeNh+fC2wrLfPoAP78RTwDftxFJAcjMcE6+biUiDW43jcHCzHBTgbmA1s9Vg2aMcB64rXBfY2rwEXD/o+DPeHd5g/YFcCz9qP7wbu9lj3uv3mLgBe91h+t/0nWPeldCejE8o5vF9eY3Y6Lj/i/gfW+Ge7gEx7WSawy378J+A6j/K77PXXAX/yWH5CuWGKPRt4G2uonVd6+3x0f7bsxxF2OfH1GRzm/Rhlf+lKj+XBeEy6R6dIsd/nV4CFwXRcgDxOTCCDchzsdTs9lp9QbrD+Qu4UVg9fx8q84H1IlnG9LO9tWBWn+Yp5xLJPF5wKrAHGGGMOAdj/ZtjF+nuMhtNvgR8DXfZzv4fdATyH9nF6PyYAlcAT9um4x0QkniA8JsaYA8Cvgf3AIaz3eT3BeVy6DdZxGGc/7rl8UAVlAhGRt+xznj3/lniU+QnWvSfPdi/yUlVvw6f4NXSKQ0ZybJ8jIgnA34DvG2PqeyvqZZnjx0JELgOOGmPWey72UrSvYXdGwnGLwDpt8pAx5lSgCetUiS8jdl/s/oElWKedsoB44OJe4hqx++KHEfn9FZQTShljLuxtvd2RdBlwgbHbbwzusCpO82d4mRFBRCKxksezxpgX7cVHRCTTGHNIRDKBo/ZyX/tVAZzbY/nKoYy7hzOAy0XkEiAG6zTQb+n/sDsj4bhVABXGmDX28xewEkiwHROAC4FSY0wlgIi8CJxOcB6XboN1HCrsxz3LD6qgbIH0RqyJqu4ELjfGHPdYNZjDqjjNn+FlHGdf9fE4sMMY8/97rPIclqbncDU32leczAfq7Gb868AXRGS0/avzC/ayYWGMudsYk22MycN6r98xxtxA/4fd8fUZHDbGmMNAuYhMsRddgDVSRFAdE9t+YL6IxNmfte59Cbrj4mFQjoO9rkFE5tvvzY0MxffXcHQUDecfUIx1TnCj/fewx7qfYF1hsQuPKxKwrnDYba/7icfyCVgfpGLgeSDa6f3rK+aR9AecidVs3uxxPC7BOu/8NrDH/jfFLi9YE43tBbYAhR51fd0+DsXA1xzcp3P57Cosr58PrFbK8/bytcCEvj6Dw7wPs4Ai+7i8hHX1TlAeE+D/A3YCW4FnsK6kCorjAjyH1XfTjtViuGUwjwNQaL8ve4EH6HHhxGD86Z3oSimlAhJyp7CUUkoND00gSimlAqIJRCmlVEA0gSillAqIJhCllFIB0QQSpkTEiMgk+/HDIvJTp2PyJCJPijUr5XC/7pUiUi4ijSJy6nC/fiiy38sJAW776efUy7qVIvKNgUWnBiIo70QPJyJShjVMQ5Yxpspj+UZgJpBvjCkbyGsYY749kO1DzK+B240xI+Wm0aBnjElwOgY1NLQFEhxKsUbTBEBETgZinQsnpOUC25wOwh/2cBxKOUYTSHB4Bmsogm43AU97FrCHYfi1iOwXkSP2aalYj/U/EpFDInJQRL7eY9tPTxfZQyK8IiKVIlJrP872KLtSRH4pIqtEpEFE3hCRNG9BizVZ0WUezyNEpErsyXBE5HkROSwidSLyvojM8FHPzSLyYY9lnqfget33Htu5ROQeEdkn1mQ+T4tIkl1HI9ZcK5tEZK+P7U8XkXV2zOtE5HR7+XkissWj3Fsistbj+YcicoX9uExE/kOsiYHqxJrkKMaj7GUislFEjonIRyJyise6MhG5U0Q2A03ekoi9L7+1j/VB+3G0x/oldv31IrJXrOF/uiczesLeplZEXvLz/X/Sfs/ftD8T74lIbiDHqrfPqQ+5vj6LInK5WJNNHbM/t9N6vI8/so9Bk4g8LiJjROQ1u663xJ7MyS4/3z4Wx0Rkk4ic67HuZhEpsbcrFZEb/Ig7NDgx/ID+9Wu4gzKsQeN2AdOwvuDKsX4pGyDPLvdbrPFyUrAmb3oZ+G973SLgCHAS1oilf7W3nWSvfxK4136cCnwJiLPreR54ySOelVhDI0zGagWtBP7HR+w/w56PxX5+KSfOUfB1+zWi7fg3eqzzjOlm4MMedXvG73PfvcTUPezDBCABeBF4xlu9XrZNAWqBr2Kd/r3Ofp6KNUxGM5BmrzuMNXhdov0+NQOpHsd0LdapyRRgB/Bte91srAH05tnH+ia7fLTHthuxBtaL9RHnL4DVWEOBpwMfAb+0183FGsb8IqwfkOOAqfa6fwLLsIY2iQTO8fP9fxJowJogKRr4nWd5f48VfXxOveznSnx8Fu1lTfZ+RmINxV8MRHm8j6uBMfZ7cBT4BGvKgWjgHeDndtlxQDXWMDwuu85q+72NB+qBKXbZTGCG098bw/b95HQA+tfHAfosgdwD/Lf9n+xNrC8pgzUhjdj/WSZ6bLcAa6RSgD/j8SVv/+fymkC8vP4soNbj+UrgHo/ntwH/8rHtJPuLJc5+/izwMx9lk+2YknrGRC9fYH3tu5fXeRu4zeP5FKyxiCI86/Wx7VeBtT2WfQzcbD/+APgi1oxxb2DNjLcIOA/Y3OOYfsXj+f/ls5nyHsL+svdYv4vPvszLgK/38ZnZC1zi8XwhUGY//hNwv5dtMrHmOvncrIK9vf8ex2qpx7oEoBPI6c+x6utz6iUun59F4KfAco91LuAAcK7H+3iDx/q/YQ1x3/38e9g/nLAGZ32mx2u/jpXc44FjWD+6vCb0UP7Tc6jB4xngfay5D57usS4dq8WwXj6b9liwfsGC9UvXcy6Lfb5eRETigPuxvvi6m/CJIuI2xnTazw97bHIc6wvjc4wxxSKyA1gsIi8Dl2P9wkNE3MCvgKvt+LsnakrD+oXsr772vacsTtz/fVjJeAzWF0xvem7bvX33RD3vYQ22WGE/rgXOAVrt5556vodZ9uNc4CYR+Z7H+iiP9eAxgZB9uuRP9tMPjDEXe4lzn8f2OcCrXvYtB6gxxtR6WeePT2MyxjSKSI39mp6THQ3a59SDr8/iCe+BMaZLRMo5cVKlIx6Pm708764rF7haRBZ7rI8E3jXGNInINcB/AI+LyCrgh8aYnX7EHvS0DyRIGGP2YXWmX4J12sVTFdYHfoYxJtn+SzKfXf1yiBPnEhjfy0v9EOtX+TxjzCis0xLgfYIafzyHdapnCbDdGFNsL7/eXnYh1rwMeb28ThPWF49VQGSsx7q+9r2ng1hfCN3GY008dsR78V637d6+O/F0J5Cz7cfvYSWQc/h8AvGlHPiVx74kG2PijDHPeZT5dARUY8yzxpgE+697MiVv+9g9F0Q5MNHH66aISLKXdb29/91yPNYnYJ2i6jn/xGB+TvtywnsgVsbKoe8fCd6UY7VAPI9JvDHmfwCMMa8bYy7CnkYWeHQAcQcVTSDB5RbgfGNMk+dCY0wX1of2fhHJABCRcSKy0C6yHLhZRKbbLYyf9/IaiVj/yY+JSEofZf2xFGuOgu9gndP2fJ1WrHPJccB/9VLHJmCGiMyyO5v/T/cKP/a9p+eAfxdrLpUE+3WXmc+mQO3Nq8BkEblerAsCrgGmY83FDVZfwxSsfoa1xphtWF9i87Baj/54FPi2iMwTS7yIXCoiiX5uD9Y+3iMi6Xan8s+Av9jrHge+JiIXiHVBwTgRmWqs+SNeA/4o1oUUkSLS/ePB5/vv4RIROVOs+Wl+Cawxxni2Pgb7c9qX5cCl9n5GYv0wasU6Rv31F6xW9EIRcYtIjIicKyLZdsf75WJNC9wKNGKdvgsLmkCCiDFmrzGmyMfqO7E6CVeLSD3wFtaXGcaY17A6L9+xy7zTy8v8FqtDsgqrk/FfA4z5EFY/welYHbTdnsY6xXAAaxKg1b3UsRurY/gtrHkSPuxRxOe+e/FnPjsdWAq0YJ3v9mdfqrFmuvwhVuL7MXCZse/PsRP7J8A2Y0ybvdnHwD5jzFEvVXp7jSLgm1jzN9Ta+3WzP9t6uJfP5vvYYsd0r13/WuBrWKcp67BaRt2/1L+K1R+0E6tT+fv2Nn29/2D9OPg51gx/cwBfVyIN1ue0V8aYXcBXgD9gfZYXA4s9jkt/6irHai3/J9Z88uXAj7C+P11Yn4eDWPt+DlZfTFjQ+UCUUgMiIk9iTZN7j9OxqOGlLRCllFIB0QSilFIqIHoKSymlVEC0BaKUUiogmkCUUkoFRBOIUkqpgGgCUUopFRBNIEoppQKiCUQppVRA/h+44clKY5EX0wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb556c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 目标y（cnt）的直方图／分布\n",
    "fig = plt.figure()\n",
    "sns.distplot(data.cnt.values, bins=30, kde=True)\n",
    "plt.xlabel('Median value of owner-occupied cnt', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb741c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 单个特征散点图\n",
    "plt.scatter(range(data.shape[0]), data[\"cnt\"].values,color='purple')\n",
    "plt.title(\"Distribution of cnt\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb87eba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.season, order=[1,2,3,4]);\n",
    "plt.xlabel('Season');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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20xXB/Rs5txtwKvAUwEIgSduBmbaqfN/U83Y/gdOA1wDnAu/b1PskSduWGccI2t3E/gvwKpq9Aw5zNzFJ2r7MNEbwHuBkYDnwS1X1o8GykiQNZqYJZW8Gfhb4A+COJPe2H/cluXeY9CRJfZtpjGCzZx1LkrY9/rKXpJGzEEjSyFkIJGnkLASSNHIWAkkaOQuBJI2chUCSRs5CIEkjZyGQpJGzEEjSyFkIJGnkLASSNHK9FYIkH02yIcmaaef2THJZkpvbxz36ii9J6qbPK4KPA8c+5tzpwKqqOhBY1R5Lkiaot0JQVV8F/uExp0+g2emM9vHEvuJLkroZeoxg76paD9A+7rWpFyZZluSaJNfcddddgyUoSWOz1Q4WV9XyqlpSVUsWLlw46XQkabs1dCG4M8k+AO3jhoHjS5IeY+hCcBGwtH2+FLhw4PiSpMfo8/bRc4C/BQ5Ksi7JqcC7gBcmuRl4YXssSZqgTW5ev6Wq6pWb+NQxfcWUJG2+rXawWJI0DAuBJI2chUCSRs5CIEkjZyGQpJGzEEjSyFkIJGnkLASSNHIWAkkaOQuBJI2chUCSRs5CIEkjZyGQpJGzEEjSyFkIJGnkLASSNHIWAkkaOQuBJI2chUCSRs5CIEkjZyGQpJGzEEjSyFkIJGnkLASSNHITKQRJjk3y7STfSXL6JHKQJDUGLwRJdgT+HHgx8AzglUmeMXQekqTGJK4IDge+U1W3VNWPgXOBEyaQhySJyRSCfYHbpx2va89JkiYgVTVswOQU4EVV9R/b41cDh1fVGx7zumXAsvbwIODbcwj3VODuLUjXeJOJZTzjGW9+4v1cVS2c7UU7zaHhLbUOeNq04/2AOx77oqpaDizfkkBJrqmqJVvShvGGj2U84xlv2HiT6Bq6Gjgwyf5JdgFeAVw0gTwkSUzgiqCqHkryO8ClwI7AR6vqxqHzkCQ1JtE1RFVdDFw8QKgt6loy3sRiGc94xhsw3uCDxZKkrYtLTEjSyG2XhSDJR5NsSLJmgFhPS/KVJGuT3JjktJ7j7ZrkqiQ3tPHO7DPetLg7JrkuyecHiHVrkm8muT7JNQPEW5BkZZKb2n/H5/QY66D265r6uDfJm/qK18b8z+3/lTVJzkmya4+xTmvj3NjX17Wxn+8keya5LMnN7eMePcc7pf0aH0kyb3fzbCLWe9r/m99Icn6SBfMVb8p2WQiAjwPHDhTrIeDNVfV04Ajg9T0vmfEgcHRVHQwcAhyb5Ige4005DVg7QJwpz6+qQwa6Re+DwCVV9YvAwfT4dVbVt9uv6xDg3wAPAOf3FS/JvsAbgSVV9UyaGzRe0VOsZwK/SbN6wMHAcUkO7CHUx/npn+/TgVVVdSCwqj3uM94a4GTgq/MYZ1OxLgOeWVXPAv4fcMY8x9w+C0FVfRX4h4Fira+qa9vn99H8EultpnQ1ftQe7tx+9DrQk2Q/4KXAR/qMMwlJngQcBZwFUFU/rqp7Bgp/DPDdqvpez3F2Ah6fZCfgCWxk3s48eTrw9ap6oKoeAq4ATprvIJv4+T4BWNE+XwGc2Ge8qlpbVXOZ5DqXWF9qv58AX6eZezWvtstCMClJFgOHAlf2HGfHJNcDG4DLqqrXeMAHgN8HHuk5zpQCvpRkdTvDvE8HAHcBH2u7vj6SZLeeY055BXBOnwGq6u+B9wK3AeuBf6yqL/UUbg1wVJKnJHkC8BJ+cvJon/auqvXQ/HEG7DVQ3KG9FvjifDdqIZgnSZ4IfBZ4U1Xd22esqnq47VrYDzi8vSTvRZLjgA1VtbqvGBtxZFUdRrNC7euTHNVjrJ2Aw4APV9WhwP3Mb7fCRrWTKY8HPtNznD1o/lreH/hZYLckv95HrKpaC7ybpivjEuAGmq5TzYMkb6P5fp49321bCOZBkp1pisDZVfW5oeK2XRiX0+94yJHA8UlupVkp9ugkn+oxHlV1R/u4gab//PAew60D1k27qlpJUxj69mLg2qq6s+c4LwD+rqruqqp/Bj4HPLevYFV1VlUdVlVH0XRx3NxXrMe4M8k+AO3jhoHiDiLJUuA44FXVwz3/FoItlCQ0/ctrq+r9A8RbOHXXQJLH0/yg39RXvKo6o6r2q6rFNF0ZX66qXv6iBEiyW5Ldp54Dv0rT5dCLqvo+cHuSg9pTxwDf6iveNK+k526h1m3AEUme0P5fPYYeB8OT7NU+LqIZTB3ia4RmmZql7fOlwIUDxe1dkmOBtwDHV9UDvQSpqu3ug+Y/33rgn2n+4ju1x1i/TNOn/Q3g+vbjJT3GexZwXRtvDfD2Ab+vzwM+33OMA2i6FG4AbgTeNsDXdQhwTfs9vQDYo+d4TwB+ADx5oH+3M2n+WFgDfBJ4XI+x/g9NIb0BOKanGD/18w08heZuoZvbxz17jndS+/xB4E7g0h5jfYdm6f6p3y9/Md/fU2cWS9LI2TUkSSNnIZCkkbMQSNLIWQgkaeQsBJI0chYCqQftiqa/Pe34eUOs3CrNhYVA6scC4LdnfZW0FbAQaPSSLG7Xe/9Iu5b+2UlekORr7fr2h7fr3V/Qrgn/9STPat/7h0l+d1pba9rFB98F/Hy758B72k8/cdq+B2e3M32liZvInsXSVugXgFOAZcDVwL+nmTV+PPBWmpmd11XViUmOBj5BMyN5U06nWUP+EGi6hmhWpv3XNMtAf41mHae/6eOLkTaHVwRS4++q6ptV9QjN0harqpl2/01gMU1R+CRAVX0ZeEqSJ29mjKuqal0b4/q2XWniLARS48Fpzx+ZdvwIzZXzxrpximZZ4Ok/RzNtAzk9xsN4Ra6thIVA6uarwKvgX7p57q5m34lbaZetTnIYzbr/APcBuw+epTQH/kUidfOHNLuYfYNmn+GpJY8/C/xGu2Pc1TR7ylJVP2gHm9fQ7Cj1heFTlrpx9VFJGjm7hiRp5CwEkjRyFgJJGjkLgSSNnIVAkkbOQiBJI2chkKSRsxBI0sj9f5dPEsJZp3csAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xbb1dba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.mnth, order=[1,2,3,4,5,6,7,8,9,10,11,12]);\n",
    "plt.xlabel('mouth');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc2cb550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.holiday, order=[0,1]);\n",
    "plt.xlabel('holiday');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xbb1d5f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.weekday, order=[0,1,2,3,4,5,6]);\n",
    "plt.xlabel('weekday');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc4256d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.workingday, order=[0,1]);\n",
    "plt.xlabel('workingday');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xbb1da58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data.weathersit, order=[1,2,3,4]);\n",
    "plt.xlabel('weathersit');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb829cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.temp.values, bins=30, kde=True)\n",
    "plt.xlabel('Median value of owner-occupied temp', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc8af4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.atemp.values, bins=30, kde=True)\n",
    "plt.xlabel('Median value of owner-occupied atemp', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd909ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.hum.values, bins=30, kde=True)\n",
    "plt.xlabel('Median value of owner-occupied hum', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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icqeIbBORbU1N+kUKhq2VrQCs0hJ5QLJSEpibn6r15CrmTKjVijGmHXgNWD/CsvuNMauMMavy8/ODFF5se7uylTl5qdoRaALWluWzpbKFvkGv06EoNWUCabWSLyJZ9utk4ErgYKgDi3U+n+HtqlbO12qVCVlblkffoO/MsAZKxYJASuSFwKsisht4G6uO/KnQhqUOneqis8+jDzon6II5ucS7hTeOaPWeih3jNj80xuwGlk9BLMrP21VW/biWyCcmNTGOFaXZbDzSDFc7HY1SU0N7doapLZWtFGYmUZKd7HQoEeeS+fnsq+vU7voqZmgiD0PGGLZWtnLerBzt2DIJa8vyAO2ur2KHJvIwdKypm6aufi6cm+t0KBFpSVEm2SnxvHFYE7mKDZrIw9Bbx1oAWKOJfFLcLuGieXlnuusrFe00kYehN4+1UJyVrFO7nYVLyvJp7OrnsE42oWKAJvIw4/MZNh9vYc3cXK0fPwsX2/XkG7QZoooBmsjDzMGGLtp6B1kzR6tVzkZRVjJz81N5Q7vrqxigiTzMvHnMSjxaP3721pbls+W4dtdX0U8TeZjZfLyFWbkpFGVp+/GzddmCfPo9vjO/HJWKVprIw4jH62PL8VbWzM1zOpSocOHcPNIT43h2T4PToSgVUprIw8jeuk66+j1arRIkCXEurlhUwIsHTuHx+pwOR6mQ0UQeRjbaLSwu0kQeNOvLC2nvHWSLPba7UtFIE3kYeeNwM+XFGeSm6fjjwXLp/HyS4908t1erV1T00kQeJrr6BqmoaeOSMp2UI5iSE9xctiCf5/c14PNpL08VnTSRh4m3jrXg8RnWaiIPuvXl02ns6mfHCZ1sQkWncccjV1Njw5FmEtwujjR2Udnc43Q4UWXdwgIS3C6e2l3Pypk6vruKPloiDxMbjjQxJz+VOJfekmDLSIrn8oUFPLGzjkFtvaKikGaNMFDT0ktVSy/zCtKcDiVqfWBlCS09A7xxWMdeUdFHE3kYGJpfcn5BusORRK/LFuSTk5rAYxW1ToeiVNBpIg8Drx9uojgrmdy0BKdDiVrxbhc3LCvipf2NtPcOOB2OUkGlidxh/R4vm442s25hvg5bG2I3ryxhwOvjqd31ToeiVFBpInfYluOt9A54uXxhgdOhRL0lRRksmJbOH7dr9YqKLprIHfbKwUYS41ysmaMDZYWaiHDLqhJ2nmhn78kOp8NRKmg0kTvIGMOrhxpZMzeX5AS30+HEhFtWzSAlwc0Db1Y5HYpSQaOJ3EGVzT1Ut/RqtcoUykyO5wMrSnhiZx3N3f1Oh6NUUGjPzin06Jaad73feNSa8KDrtOevlqnJGe863ra6lI9dOJOHN1fz2601fPbysglvr1S40RK5gw41dFKQnkh2qjY7nErzCtJZW5bHw5urtaenigqayB3SN+ilqrmXBdO0E5AT7rhoNqc6+3lyV53ToSh11jSRO+TwqS68xrCoMMPpUGLSpfPzWVSYwX2vHNXZg1TEGzeRi8gMEXlVRA6IyD4R+YepCCza7a/vJDXBTWluitOhxCSXS/iHK8o43tzDk7u1VK4iWyAlcg/weWPMIuAC4G4RWRzasKKbx+vjUEMXiwozcGlvTsdctXgaiwoz+J+XtVSuItu4idwYU2+MqbBfdwEHgOJQBxbNjjf30O/xsVirVRylpXIVLSZURy4is4DlwJYRlt0pIttEZFtTkw4VOpb99Z0kuF3M1WFrHXfV4mksLszg+y8epm/Q63Q4Sk1KwIlcRNKAx4B/NMZ0Dl9ujLnfGLPKGLMqP1+nKxuNzxgO1HdSNi2NeLc+a3aayyXce80iTrSe5lebqpwOR6lJCSiTiEg8VhJ/xBjzp9CGFN1Otp2mq8+j1Sph5OKyPK5YWMCPXz1KV9+g0+EoNWGBtFoR4BfAAWPM90MfUnTbX9+JS2DhdE3k4eTeaxfRN+jlpQOnnA5FqQkLpER+EfAR4HIR2Wn/uybEcUWt/XWdzM5L1UGywszc/DQ+smYm26raqG3rdTocpSYkkFYrG40xYoxZaow51/73zFQEF20au/po6u7XapUw9Y9XzictKY7Hd5zE6zNOh6NUwPRp2xQ6UN8FoL05w1RmcjzXLy2ivqOPTfaAZkpFAk3kU2h/XQfFWclkpeggWeFqSVEGiwozePngKVp7dG5PFRk0kU+Rxs4+TrSd1tJ4mBMRblhWhEuEP+88iTFaxaLCn45HPkVetFtDLC7SRO6kQMZ9z0yO56ol03lyVx07T7SzvDR7CiJTavK0RD5Fnt93ipzUBKalJzodigrA6tk5zMhO5uk99fT0e5wOR6kxaSKfAh29g7x1rJklhRmIDpIVEVwi3LSihP5BH0/vqXc6HKXGpIl8Crx44BSDXkN5cabToagJmJ6RxCXz89l5op2DDX81KoVSYUMT+RR4Zk89xVnJlGQnOx2KmqB1C/KZlpHI4ztOcnpAB9VS4UkTeYh19g2y4UgTV5dP12qVCBTndnHzihn09Ht4Soe6VWFKE3mIvbTfqla5+pxCp0NRk1Scncyl8/PZcaKdl/brWCwq/GgiD7Fn9jRQmJnE8hlZToeizsK6hQVMz0jinsf30N6rHYVUeNFEHkJdfYO8caSJ9eXTcbm0WiWSxblcfGBlCW09A3z9yf1Oh6PUu2giD6FXDjYy4PFxrVarRIXirGQ+s24ej+84yYtaxaLCiCbyEHp6dz3TMhJZoT0Do8Zn181jUWEG92oViwojmshDpLvfw2uHm7i6vFCrVaJIQpyL792ylLaeAb72xD6nw1EK0EQeMkPVKleXT3c6FBVkS4oyuXvdPP68s44X9jU4HY5SOmhWMPkPyPTIlmrSE+M40tjNsaYeB6NSoXD3unm8sP8U9z6+l5Uzs8lN0zF0lHO0RB4CAx4fh091sbgoA5d2AopKCXEuvv83y+g8Pcg//3G3DnerHKWJPAQOnepi0Gs4R8dWiWqLCjP40tULeflgIw++WeV0OCqGaSIPgT217aQmxjErL9XpUFSIfeKiWaxbkM+3nj3I/jodWEs5QxN5kPUNejnY0MU5xZlarRIDRITv3rKMrOR47vr1dm2SqByhiTzI9td34vEZzi3RapVYkZeWyE8+vJKGjj7+7jc78Hh9ToekYoy2WgmyXSfayU6JZ0ZOitOhqBAYa6q4a5cW8viOk/zHcwf5l2sXT2FUKtZpIg+i7n4Px5q6WVuWr0PWxqDzZuWQkRTHzzZUkpuWyF2XznU6JBUjNJEH0Z6THfgMLNORDmPWV65fQlvvIN959iCpCW4+smaW0yGpGKCJPIh2nWhnekYS0zOSnA5FOcTtEv7rb5bRO+DlX/+yj75BH59aO1v/QlMhpQ87g+REay81rb0s04ecMS/e7eK+25ZzzTnT+eYzB7j38T0M6gNQFUKayIPkSXsasKUlWq2iICnezX23ruDudXP5zdYTfOj+zRxv6nY6LBWlxq1aEZFfAtcBjcaY8tCHFJme2FlHaU4K2akJToeiwoTLJXzhvQuZPy2df/3zXq7+0QY+f9V8Pn7hbBLiRi5DjdUqBuC21aWhCFVFuEBK5A8A60McR0Q71NDFwYYufcipRnTjucW8+LlLWVuWx7eeOcjl//Uaj22vxevT8VlUcIybyI0xbwCtUxBLxHpi10ncLtGxVdSopmUk8bOPruLBO84nKyWez/9hF+t/+AbP7W3QAbfUWdM68rNkjOEvO+u4aF4eaYnaCEiNTkS4dH4+T9x9Mf97+wq8xnDXr7dz4483seFIkyZ0NWlByzwicidwJ0BpaezU41XUtFPbdpp/unI+/R5tmaDG5l8H/okLZ7PzRBsvH2jkI7/Yyuy8VK5fVqTNV9WEBa1Eboy53xizyhizKj8/P1i7DXt/qqglKd7FVUumOR2KijBul7ByZg6fe898rltayKnOPn78ylFePngKj08LBSpwWhdwFvoGvTyxq46rywtJT4p3OhwVoeLcLi6cm8fSkiye2l3HywcaOdTQxe2rZ5KZrJ8rNb5xS+Qi8hvgLWCBiNSKyCdDH1ZkeH5fA119Hm5ZVeJ0KCoKpCXG8aHzSrnt/FIau/q579WjVDXrNIFqfIG0WrnVGFNojIk3xpQYY34xFYFFgj9sq6UkO5kLZuc6HYqKIuXFmXz60rkkxbn4xcZK9p7scDokFea01cok1bb1sulYMzevLMHl0nE0VHBNy0jiM5fNozg7md++XcOOmjanQ1JhTOvIJ+mx7ScBuHmlVquod4zXM3MikhPcfOKiWTy8uZo/bK/FZ4z27FQj0hL5JHh9ht9vO8GFc3MpydYJJFToJMa5+diaWcwrSONPFSd5cf8pp0NSYUgT+SS8dqiRk+2nuX31TKdDUTEg3u3i9tWlFGcn89lHK9hyvMXpkFSY0UQ+CQ+9Vc20jETes1jbjqupMVQyL85O5lMPbWN/XafTIakwool8gqpbenj9cBO3nl9KvFsvn5o6qYlxPPzJ1aQmxPGxX22lpqXX6ZBUmNBMNEGPbKnB7RJuPV8fOqmpV5yVzMOfPJ8Bj4+P/HILTV39ToekwoC2WpmAB9+s4uG3qlk0PZ2XDzQ6HY6KQUOtYm49bwa/2FTJDfdt5G/XziEp3n1mHW3ZEnu0RD4BFTVtnB70csEc7QCknFWam8rtq2fS2NnPQ29V6VRyMU4TeYC8PsPGI80UZyUzOy/V6XCUYv60dG5ZVUJ1Sy+/2VqjE1XEME3kAXpubwMtPQNcOj9fZ0RXYWNpSRY3nFvEwYYuHquwOg2p2KN15AEwxvDT14+Rm5rA4qIMp8NR6l1Wz86ld8DLi/tPkZzg5vbVpVrYiDFaIg/ApqMt7DnZwSVl+bj0C6LC0GXz87l4Xh5vHWvhy3/ei0+rWWKKlsjHYYzhv18+QkF6IstLdXJlFZ5EhKvLp+MS4ZEtNXT1efjeLctIiNOyWizQuzyOlw80srWqlb+/oow47QCkwpiIsL58Ol9cv5AndtXx4V9oO/NYoZlpDF6f4T+eO8icvFQ+eN4Mp8NRKiCfvmwuP/rQueyubef6/9lIhQ6BG/U0kY/hsYpajjR284X3LtDu+Cqi3HhuMY99+kLi3MItP32L/3juIH2DXqfDUiGideSj6On38IMXD7NsRhbry6c7HY5SE7akKJOn/24t33h6Pz957RjP72vg3qsXccWigjFbtYw3prr2HA0/WswcxXefP0RDZx9fuW6RNuVSESszJZ7v3rKMh+44H5/P8KmHtnHzT9/i9cNNGG1zHjU0kY9ge3UbD75VxUcvmMnKmTlOh6PUWbtkfj4vfu5SvnXTOdS29fKxX27lyu+/zoNvVtHRO+h0eOosaSIfpt/j5YuP7aYwI4kvrF/odDhKBU2828Vtq0t545/X8YMPLiM1MY6vPrGP8775Enc/UsGrBxvx6JgtEUnryIf5zrMHOdrYza8+cR5piXp5VPRJjHNz0/IS3nduMfvqOvnj9lr+svMkT++pJz89kYXT0lkxM5tpGUlOh6oCpJnKz58qavnVpio+cdEs1i0ocDocpUJKRCgvzqS8OJN7r1nEq4ca+eP2Wl4+cIoNR60B4laUZrGsJIsULdSENb07tr0nO7jnT3u4YE4O916zyOlwlJq08VqdjGXdggLOm5XDrhPtVNS08eTuep7Z08DCwnRWlmZTNi09iJGqYNFEDhxt7OKOB94mNzWB+25boW3GVUxLS4zjonl5XDQvj7r20+yoaWPniXb21XWSnhhHW+8At60uJS8t0elQlS3mE/mhhi5u//lmQHjgjvP1w6mUn6KsZIqykllfXsihhi62VrXw/RcPc9+rR3nfuUXccfFsFk7XEUGdFtOJ/M1jzXz20R3EuYRH//YC5hWkOR2SUmHJ7RIWF2WwuCiD82fn8MCblfxxey2/31bLRfNyueOi2axbUIDLpX0unBCTdQhen+EHLx7m9p9vISs5nt/9nzWaxJUK0LyCNL7xvnPYfM8VfHH9Qo439fDJB7dxhd0uvaff43SIMSfmSuSbjjbzrWcOsK+uk/evKObfbywnVZ/IKzVhWSkJfPqyuXxq7Wye29vALzdV8tUn9vG9Fw7x/uXF3LSihGUlmdozegoElMFEZD3wI8AN/NwY850CsFA/AAAPsElEQVSQRhVkg14fLx9o5Nebq9loN6v6n1uXc/2yIqdDUyrixbtdXL+siOuXFVFR08YDm6r4zdsnePCtamblpnDVkulcsbCAFTOztSFBiMh44y2IiBs4DLwHqAXeBm41xuwfbZtVq1aZbdu2BTPOCWvs6mNrZSsbDjfz8sFGmrv7mZaRyCcvns1H18wiKd79V9ucTbMtpZTlttWldPYN8uyeep7aXc/m4y0Meg3J8W5WzMxi+YxsFhVmsGB6GiXZKSN+F8cSrYN6ich2Y8yqyWwbSIn8fOCoMea4fbDfAjcCoybys2WMwWfA4/Ph9Rk8PoPXa//vMwx4fHT2DdJxepDO09b/LT0D1Lb1cqL1NAcbOmnuHgAgIymOtWX5fGBlMZeU5evkEEpNgYykeD54XikfPK+Urr5BNh1tZvPxVrZUtvKT14/h9ZuKLi8tgeyUBFIT40hLjCMlwX2mutPjM/h8Bo/Ph8drGPD6qG07jcf7Tm4Yygserw+vMXz7mQPEuYU4t4t4lxAf5yIpzk1ygpsU+19yQhwp8SP8bOh1vJuUhLgzy1P9XifEuXCJ4BLCptookEReDJzwe18LrA5FMMu+/gI9/R48k5xvMDc1gZLsZNYtKGBRYQbLS7M4pzhTk7dSDkpPimd9eSHrywsB6Bv0crSxmyONXdS2nuZk+2k6Tg/S3e+hp99DU1c/PQMeXCK4Xda/OJfgEiEhzoUxkBjvJs5vWZzLhdttvV4wPR2P10r+g17DoNdH36CX3gEvpwe8tPcOcnrQS++Ah95+L72D3nf9Ypkol2AndiE/PZFNX7o8WJcuYIEk8pF+5fzVWYvIncCd9ttuETl0NoFNRjVQ8dc/zgOapzqWENDzCC/RcB4hOYfbg73D8YXNvTgCyD2T3nzBZDcMJJHXAv7znJUAdcNXMsbcD9w/2UBCRUS2TbbeKZzoeYSXaDiPaDgHiK7zmOy2gdQ5vA2UichsEUkAPgQ8MdkDKqWUCq5xS+TGGI+IfBZ4Hqv54S+NMftCHplSSqmABNSO3BjzDPBMiGMJlbCr7pkkPY/wEg3nEQ3nAHoe47cjV0opFd60XZ5SSkW4qEjkIrJeRA6JyFER+dIIyxNF5Hf28i0iMmvqoxxfAOdxiYhUiIhHRG52IsZABHAenxOR/SKyW0ReFpGZTsQ5ngDO4y4R2SMiO0Vko4gsdiLO8Yx3Hn7r3SwiRkTCsgVIAPfj4yLSZN+PnSLyKSfiHE8g90NE/sb+juwTkUfH3akxJqL/YT2APQbMARKAXcDiYet8Bvip/fpDwO+cjnuS5zELWAo8BNzsdMxncR7rgBT79acj+H5k+L2+AXjO6bgncx72eunAG8BmYJXTcU/yfnwcuM/pWINwHmXADiDbfl8w3n6joUR+ZggBY8wAMDSEgL8bgQft138ErpBw6Vv7jnHPwxhTZYzZDYTzVOeBnMerxphe++1mrL4J4SaQ8+j0e5vKCB3lwkAg3w+Afwf+E+ibyuAmINDzCHeBnMffAj82xrQBGGMax9tpNCTykYYQKB5tHWOMB+gAcqckusAFch6RYKLn8Ung2ZBGNDkBnYeI3C0ix7CS4N9PUWwTMe55iMhyYIYx5qmpDGyCAv1cfcCusvujiMwYYbnTAjmP+cB8EdkkIpvt0WfHFA2JPJAhBAIaZsBhkRBjIAI+DxH5MLAK+G5II5qcgM7DGPNjY8xc4IvAl0Me1cSNeR4i4gJ+AHx+yiKanEDux5PALGPMUuAl3vkrPJwEch5xWNUrlwG3Aj8XkayxdhoNiTyQIQTOrCMicUAm0Dol0QUuoKEQIkBA5yEiVwL/AtxgjOmfotgmYqL347fA+0Ia0eSMdx7pQDnwmohUARcAT4ThA89x74cxpsXvs/QzYOUUxTYRgearvxhjBo0xlcAhrMQ+Oqcr/4Pw8CAOOA7M5p2HB0uGrXM3737Y+Xun457Mefit+wDh+7AzkPuxHOuBT5nT8Z7leZT5vb4e2OZ03GfzubLXf43wfNgZyP0o9Ht9E7DZ6bgneR7rgQft13lYVTG5Y+7X6RML0sW5Bmvyi2PAv9g/+zes0h5AEvAH4CiwFZjjdMyTPI/zsH5b9wAtwD6nY57kebwEnAJ22v+ecDrmSZ7Hj4B99jm8OlaCDOfzGLZuWCbyAO/Ht+37scu+HwudjnmS5yHA97HmfNgDfGi8fWrPTqWUinDRUEeulFIxTRO5UkpFOE3kSikV4TSRK6VUhNNErpRSEU4T+VmwR4qbZ7/+qYj8q9Mx+RORB0TkGw4c9yYROSEi3Xb3b3WW7Gs5Z5LbnvmcnsXx94nIZZPc1pHP4WhE5DIRqXU6jmAKaIagSGf3WCsCiowxzX4/3wksA2YbY6rO5hjGmLvOZvso8z3gs8aYvzgdSLQwxqQ5fPwlTh5fjS2WSuSVWOMWACAi5wDJzoUT1WZidcwIe/aQDUpFtFhK5A8DH/V7/zGscb3PsCeg+J6I1IjIKbu6JNlv+RdEpF5E6kTkjmHbnvnzUUSyReQpe5D7Nvt1id+6r4nIv9ujm3WJyAsikjdS0CJyQESu83sfJyLNIrLCfv8HEWkQkQ4ReUNERiw52YPubxz2M/+qoTHPfdh2LhH5sohUi0ijiDwkIpn2PrqxxlzeZY8KONL2F4rI23bMb4vIhfbP14nIHr/1XhKRrX7vN4rI++zXVSLyf+2R7jrEmjgkyW/d6+zJBdpF5E0RWeq3rEpEvigiu4GekZK5fS4/tO91nf060W/5jfb+O0Xk2NAIdSKSIyK/srdpE5E/B3j9H7Cv+Yv2Z+J18ZtwYyL3aqzP6bDjT/R6X2m//pqI/N6+711iVbus8ttuuVgToHSJyO+welYPLcuzvw/tItIqIhvEGrhr6Bj3iDWhQpt9HQO9p0Ui8phY37lKEfl7v2XJ9vVtE5H9WD2ko4vT3VWnqEtsFXAl1uAzi7ASzQmskqPBGjEN4IfAE0AO1mBCTwLftpetx+pWXo419vSj9rbz7OUPAN+wX+cCHwBS7P38AfizXzyvYXXPnY/1V8FrwHdGif0rwCN+768FDvq9v8M+RqId/06/Zf4xfRzYOGzf/vGPeu4jxHQH1nAHc4A04E/AwyPtd4Rtc4A24CNYVXu32u9zsb7wp7HGl4gDGrAGFEq3r9Np7DEn7Hu6FavKLAc4ANxlL1sBNAKr7Xv9MXv9RL9td2INXpQ8Spz/hjVWegGQD7wJ/Lu97HysoZDfg1UYKsbuDg48DfwOyAbigUsDvP4PAF3AJfa9/JH/+oHeK8b5nA47/kSv95X2669hjVt+jX19v409rgnW+CHVwD/Z538zMMg7n8NvAz+1l8UDa3ln7uAqYK99X3KATX7bjXpP7XuwHeu7koD1uTwOvNfe9jvABnufM+xj1Dqdl4Ka45wOYEpO8p1E/mX7g7QeeNH+8BqsmXcEawyTuX7brQEq7de/xC/ZYiXhERP5CMc/F2jze/8a8GW/959hlNllgHlYX/ChGXUeAb4yyrpZdkyZw2NijEQy3rmPcJyXgc/4vV9gf1nj/Pc7yrYfAbYO+9lbwMft1xuA92ONwvcC8Hv7fq0Ddg+7px/2e/+fvDMw2k+wk67f8kO8k1SrgDvG+cwcA67xe/9eoMp+/f+AH4ywTSHWpB/ZIywb9fr73avf+i1LA7xY44QHfK/G+5yOENdErrd/In/Jb9li4LT9+hKsXwbit/xNv8/hvwF/GSke+xh3+b2/Bjg23j3FSu41w5bdA/zKfn0cWO+37E6iLJHHWv3gw1jTWc1mWLUKVqkrBdgu70weJFi//cEq+W33W796tIOISArWGM/rsUpmAOki4jbGeO33DX6b9GJ9cf+KMeaoiBwArheRJ7GmFFtuH8cNfBO4xY5/aOagPKwSY6DGO/fhinj3+Vdj/VKcBpwc51jDtx3afmhw/dexxmGutV+3YX1Z++33/oZfwyL79UzgYyLyd37LE/yWg9/g/iJyO1ZyBthgjLl6hDir/bafATwzwrnNAFqNPbPLJJyJyRjTLSKt9jH9JyII2ufUNpHr7W/4tU+yq6iKgJPGzpgjxPBdrF8EL9jx32+M+Y7f8hPDtgvknnqBIhFp91vmxvolBX99Dce7JhEnlurIMcZUYz30vAarOsBfM9afkkuMMVn2v0zzTmuBet49jnDpGIf6PFYpdbUxJgOrlAIjDyofiN9gVUHcCOw3xhy1f36b/bMrscZYnzXGcXqwEoC1gsh0v2XjnftwdVhfrCGlgAfrT/rxDN92aPuhXwBDieUS+/XrWInlUsZOLP5OAN/0O5csY0yKMeY3fuucSTTGmEeMMWn2v6tHibOUd8aNPgHMHeW4OTLyJABjXf8hM/yWp2FVBQwfqzqYn1MIzvX2Vw8Ui7xrKsUzMRhjuowxnzfGzMEa+vdzInKF37rDY/e/5qPd0xNYf5H4L0s3xlzjF9NErknEialEbvskcLkxpsf/h8YYH9Zg9D8QkQIAESkWkffaq/we+LiILLZL3F8d4xjpWF+2dhHJGWfdQPwWuApromL/GbXTsUpOLVhJ4ltj7GMXsEREzrUfIH1taEEA5z7cb4B/EpHZdsL5FtYEyp4AzuUZrGmsbhPrwe0Hsf40H5pm7E2sX4LnY1XB7MNKqKux/poKxM+Au0RktVhSReRaEUkPcHuwzvHLIpIv1oPorwC/tpf9AviEiFwh1oPfYhFZaIypx5q27n/FeuAdLyJDv8RHvf5+rhGRi0UkAWsOzS3GGP+SZLA/pxCc6+3vLaxf6n9v39/32/vGjvU6EZlnJ/pOrNK012/7u0WkxP7e3Iv1vAHGvqdbgU6xHmAni4hbRMpFZOih5u+Be+x7UgL4l+qjQswlcmPMMWPMtlEWfxHrId5mEenEGjd7gb3ds1gPmV6x13lljMP8EOthUTPWA7PnzjLmeqwvyIW888EGq3qoGqs0u98+1mj7OIxVP/kScATYOGyVUc99BL/knWqqSqwHXwF9OYwxLcB1WH+1tAD/DFxn7Pb99i/YCqyx1gfszd4Cqk0Ak9Da+9iGNYHtfVhVBUex6qgn4hvANmA31pjQFfbPMMZsBT6BVX3WgVVyHSq9fwTrecFBrIdz/2hvM971B+uX9FexZq9aCdw+SmzB+pwG5XoP298AVp37x7Gu/Qd591+/ZXa83fZx/tcY85rf8kex6uqP2/+Grvmo99Surrwe61lUJdb37udYf6UCfB3re1Jp7/vhiZ5XuNPxyJUKAyLyANYDuHCc93NKiNVx71PGmJecjiXSxFyJXCmloo0mcqWUinBataKUUhFOS+RKKRXhNJErpVSE00SulFIRThO5UkpFOE3kSikV4TSRK6VUhPv/fCMpdz/qKdcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd91ee48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.windspeed.values, bins=30, kde=True)\n",
    "plt.xlabel('Median value of owner-occupied windspeed', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd91e198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.casual.values, bins=30, kde=True)\n",
    "plt.xlabel('Median value of owner-occupied casual', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd8eb668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.registered.values, bins=30, kde=True)\n",
    "plt.xlabel('Median value of owner-occupied registered', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "#get the names of all the columns\n",
    "X = data.drop(['instant','dteday','yr','cnt','casual','registered'], axis = 1)\n",
    "\n",
    "cols=X.columns \n",
    "\n",
    "# Calculates pearson co-efficient for all combinations，通常认为相关系数大于0.5的为强相关\n",
    "data_corr = X.corr().abs()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10, 10)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_corr.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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TjLhjcRnaVatdjSe7t2PY8+85pnjkJHFHTzpNxynqU5T4PzLmvOeRe2nVvQ0fdxmeac74Y/FE7z7MXbUqu7Rej0tOcu3DQzzaObcsazdQnZRO+gigNRBpWZZ/6qOqZVkXJkZOBLqnjoYPBvKkHuMlUjrxpYEtxpiiZPoe2yFtDzAJ3U7yuqviV5TfT/5JTPxfnE9MYkHEIere7fzC5lMoH+v2pXRq9x87xbnEJArfkpuY+L8cXwA9kvAXh06cxrfQLW7PkJUNG7ZSoUI5ypYtjZeXF23btiQ4eJFTm+DgRXTo8CQArZ9ozvLlnp3ScKXCN2zJkG1u8EKnNnODF17M1ro5y1KzzQ1eSNu2LfH29qZs2dJUqFCO9eGbKVasCAULFgAgT548NGzwKLt27XNvsEtIOZ9lL2Z+skXm57N9yp0hnrjC8zloUC8KFsjPWz0HuaLsq5b+efvkk0GZ5mzvyNmM5ctXX/a4xYundH4LFSpI164dmDAh+3zSeGTrfoqUK0nB0sWxedmpHPQguxc5T3MoXPbi1J6KDfyJP5hyTSpYurjjC6AF/IpR9A4fEqKPkx3FZpJz76JNTm3S5qyQJufUJ9/jy9pv8mXtN9kwfgFrxs5h0yTn50V2sWfrbnzK+XJb6RLk8srFo0F1WL9onVObclXuoNuI7gx7/j1OnTyVxZGyt31b91CynA/FS9+G3SsXDwXVZuOi9U5tylYpR5cRL/Px88M5nSZnkZJF8crtDcAtBW7hrhp3E7vvCJLzeLRjaozxBeIsy5pijPkL6AoUN8Y8ZFnWGmOMF3CnZVmRQH4gNnXds0BM6jHKW5a1DlhnjAkipZMemtpmqTHmTuB2YBdwv7szXo1eA98nfPM2EhJO07BVe15+vgOtg3LerZBy2W30CaxBt0lLSU62aHl/eSqUKMQXS7ZS2bco9SqVokfT6gyZvZapq3eCMQx+4iGMMWw+dIzxoVHkstuwGegbWJPCt+S5/C91k6SkJN54411Cgqdis9uYNHE6UTt2M3BATzZu2kpw8CImTJjGxAmfERUVRnxcAu07XLxt3e5dayhQID/e3l60CGpC8+bPsGPnHkYM70e7dq3Ily8v+/eFM2HCj7w31L13FkhKSuL1N/ozL+QH7DYbEydNJypqN4MG9mTDxpRs4ydMY9LE0eyMCiM+PoFn2qdki4razcyZc4nYuozEpCRee70fycnJ+PiUYPx3o7DbbdhsNmbOnEvIvMUAdH/lf/R862VKlizO5o2L+W3+Ul58qZfbM7/xxrsEz52C3W5n4qTp7NixmwED3mLTxm0EhyxiwsRpTBg/iqjIlcTFJdDhuYu3mNy1azUF8qecz6CgJjQPfJY///yTvn1eY+fOPaxb+xsAX341kQkTprk1W1oXcs6dOxm73c4kR84ebNwYQUjIIiZOnM748aOIjAwlLi6B557r7th/165V5E+TMzCwPTt37uGTTwZRtWrKyNzw4aPYu/eApyJmYCUls2DARJ7+/m1sdhtbZ6zgxJ4Y6vRoTey2A+xZvIkaHQMoV/seks8n8e/pv5nT4ysASte4i4dfDiL5fBKWlcz8/hP4N/4vDyfKnJWUzMIBk2j3fW+M3ca21JyPpubcu3gT1TsGUKZ2FZLPJ3Hm9N+E9Pja02VfteSkZMa9+xWDJg/BZrexZPoiDu/+nWd6PMveiD2sX7Sezv3+R958eej9ZcrtS08cOc6w51PujjV85geUKl+KPLfk4bt1E/m812g2h2661K/0iOSkZCYO+Ia+3w/EZrezfMZiovccpk2PpzmwbS8bF4fzzDudyJMvD69/0RuAk0eO83GX4fhVKEX7/p2xLAtjDMHjZnN41yEPJ3KxG/Q+58aTc2GNMU2Aj4Bk4DzQDUgERgMFSXnzMMqyrG+MMd2A3qRMUYkA8luW1ckYMwuoSMpo+RLgDSA38BUpo/KJQA/LspYZYzoBNSzL6p76+4OBjy3LWp5VjedP7M/+k4Wvk8SlUzxdgssV7DDO0yW4RXIOmON+Pdhtnp6Z5x7Z7a5FrvJuiUc9XYJb2G+S87nGyv7T+a6HfObm+QD+x0O/Zqsn79kdy1z6Ype7Un2P5PXoM8qyrAXAgkw21cmk7ZfAl5msz3iHfjgDdMqk7URSpsdcWPbsjaVFRERE5Np48F7krnRzDDuJiIiIiOQAN89nMSIiIiJy47hB55xr5FxEREREJJvQyLmIiIiI5Dw36Jxzdc5FREREJMexrOzzP4hfT5rWIiIiIiKSTWjkXERERERyHn0hVEREREREXEkj5yIiIiKS89ygXwjVyLmIiIiISDahkXMRERERyXk051xERERERFxJI+ciIiIikvMk6z7nIiIiIiLiQho5FxEREZGcR3PORURERETElTRyLiIiIiI5j+5zLiIiIiIirqSRc3HI1aC9p0twub9j2pO/VD1Pl+EGN+ZoQnrJN+ioSXr5c+fzdAlusYW/PF2CW+TCeLoEt/A2dk+X4BZnrBvzjiE5wg0651yd88tIXDrF0yW4xc3QMRcRERHJ7tQ5FxEREZGc5wb99FRzzkVEREREsgmNnIuIiIhIzqORcxERERERcSWNnIuIiIhIjmPdoHfKUedcRERERHIeTWsRERERERFX0si5iIiIiOQ8N+h/QqSRcxERERGRbEIj5yIiIiKS82jOuYiIiIiIuJJGzkVEREQk59GccxERERERcSWNnIuIiIhIzqM55yIiIiIi4koaORcRERGRnEdzzkVERERExJU0ci4iIiIiOY/mnIuIiIiIiCupc+5mq/YcoeWoOQSNnM340MgM22MT/qbL+MW0GzuPJz8PYeXuGAAiok/Qduy8lMfnISyNOuzu0q+b/sM/pU7zp2jV/iVPl3JNGjeuy7Zty4iMDKVnz5czbPf29mby5LFERoYSGjqbMmVKAVCkSCEWLJjGiRM7GDlyiNM+bdoEER6+gE2bFjNs2DtuyZGZgIB6bI9YQVRUGL16vpJhu7e3N1OnfEFUVBhhK+c6sgH07vUKUVFhbI9YQePGdR3ru3d/ns2bFrNl8xJeffV5x/p3+/fgwP4NhK9fQPj6BTRt2sC14dIICKjH9u2h7IgKo1evLHJO/ZIdUWGsCkuXs3d3dkSFsX17qFPOPbvXsnnTYjaEL2TtmnmO9ffeW5mVoXPYvGkxv/wykfz5b3VtuCw0bPQo6zYtYMOWxbzeo2uG7d7e3nw3cRQbtixm0dKZlL7dz2m7Xykffo/dQvfXnndab7PZWB42mx9/GufS+q+Ff937+GzpF4xZ8RWturXOsD2wSwtGLv6cj+d/xoAfhlDMrzgAZSuXY9gvH/DpojF8PP8zHg6s7e7Sr0q1uvfxydKxjFzxJS26PZFhe7MuLfho8Rg+mD+KfmlyFvMrzrDgTxgxbyQfLRpNo2ebuLv0q3KznM/76t7P58u+5IvQr3ni5TYZtrfo0pLRS8YycsFoBv84lOKpOQHe/X4QUyJ+pN+EAe4s2XOSk1378JAbunNujClkjHk5zXI9Y0ywp+pJSk5mxNxwxj5Xn1mvBjJ/20H2HTvl1OabFdsJuOd2pr/SjPfb1mb43HAAKtxWiB9easqMV5oxtmMD3puzjsSknPlxTqtmjfnq06GeLuOa2Gw2PvtsKC1bdsTfvyFt27bg7rsrOrXp1KkdCQmnqFKlDmPGfMvQoX0BOHPmLIMHf0KfPsOc2hcpUogRI97hscee5v77G1GiRDHq13/EbZkuuJAtqEUHqlWrT7t2LamULlvnzk8Rn3CKypVrM3r0NwxPfSNR6e6KtG3bEn//BgQGtWf06GHYbDaqVL6L5//3NA8/Ekj1GgE0a9aIChXKOY43esw31KzVhJq1mjB//lK35Rz92TCCgtpzb7X6PNWuFZUqOef8X+enSYg/RaXKtfls9DcMH94vJWelirRr25Jq/g0IDHyWMaOHY7NdvIw2avwkNWoG8OBDzRzrvv7qI97pN5z77m/E7F9/4623urklZ1o2m40PPxlE2ye68FDNx2jdJpC77qrg1Kb9c21ISDhNDf9GfDl2AoOG9HLaPvz9fixZFJrh2C+93JHdu/a5tP5rYbPZeP69FxnWcTBvNurOIy0epVTF0k5tDkQe4O3AHvRs+jpr562mQ99OAJz99yxj3hxFj8avMuy5wXQa+Dz5CtzigRSXZ2w2Or/3Ih90HELPRq/ycItH8atYyqnNwcj99At8i7ebvsG6eat5pm9HAOKPxTPwibfp2+xN+rfsTYturSl8W2FPxLism+V82mw2ug59ifc6DuK1hq9Qu0WdDDn3R+6nZ/MevNnkNVaHrOK5dzo7tv369SxGvfmpu8uW6+yG7pwDhYCMQ5sesj36JKWL5qdUkfx45bLTpGoZlu9wHgE3wN9nzgPw15lzFM+fF4C83rnIZU85XecSkzAYt9Z+PdXwr0rBAvk9XcY1qVnTn337DnLgwO+cP3+en36aS1BQgFOboKAApkyZCcCsWfMcHe1//vmX1avDOXv2jFP7cuVuZ8+eA5w4EQfA0qVhtGr1mBvSOEufbcaM2Zlmmzz5JwB+nhVC/fq1HetnzJjNuXPnOHjwMPv2HaRmTX/uvrsC69Zt5t9/z5CUlMTK0LW0bNnU7dnSqlXzPqec02fMJijIecTQKefPITRw5GzC9HQ5a9W875K/7847y7Ny5VoAFi9ZyeOPN7tke1eoXuNeDuw/xKGDhzl//jyzfg7hscCGTm2aNW/EtB9mATD71/nUqffQxW2BjTh48DA7d+xx2sfXtySNm9Rj8qQZrg9xlSr4V+TowaMcO/wHiecTWTV3JTUa13JqE7kmgnNnzgGwe/MuivgUBSD2wBGOHowFIP5YHKdOnKJAkQLuDXCFUnLGcuzwHySdT2TN3DBqNH7AqU3Umu2OnHvT5Ew6n0jiuUQAvLy9MLbs+7pys5zPiv4ViT0Yyx+/p+QMmxtKrQDn87l9TQTnzpwFUnIWTc0JELFqG//+9a9ba/YoK9m1Dw/J9p1zY0xZY8xOY8y3xpjtxpipxphGxphVxpg9xphaxphBxpjxxpjlxpj9xpjXUnd/HyhvjNlijPkodd2txpiZqcecaoxx29Xo2Ol/KVkwn2O5RMF8HPvT+Y/opQb3ErL1AAEfzaL75OX0aV7DsS3i8AmeGB1Mm89D6N+ilqOzLu7j61uS6OgjjuWYmFh8fUtk2SYpKYnTp/+kaNGsR6P27TvEnXeWp0yZUtjtdoKCAihVytc1AS7Bz9eH6MOxjuWYmKP4+vmka1OS6OiUNklJSZw6fZqiRQvj6+fjWA8QE30UP18fIqN28eijD1CkSCHy5s1D06YNnLJ1e6kTGzcsYtzXH1OoUEEXJ0zh65fxHPr5lszQ5nCac3jqVEpOv8zOv1/KvpZl8du8H1m39je6PP+so01k5C7Hm5w2rQMp7YFz6+NTkpiYi+fnSMxRfHycn7c+viWIiT4KpD5vT/1FkaKFyZcvL6+/2ZUPR4zJcNzhH/Rj0LsfkpwNv5RVpGRRTsaecCzHxZ6kaMmiWbZv2K4xm5dvzLC+QrWK5PLOxR+Hjrqkzv+qcMkiTjlPxp6kcMkiWbav164RW5dvciwX8SnGB/NH8fnab5nz1Szij8W7tN5rdbOczyIli3LiiPP5LFoi65yN2jVm07KMOSVnyym9uwrAZ8C9wN3AM0BtoCdwYYLu3UAToBYw0BjjBfQB9lmW5W9Z1oXPaO8D3gAqA3cAGeYPGGO6GmM2GGM2fLd4w3ULYWFlWJf+ncH8bQdpcX95FvZ6gs871KP/z6tJTk7Zr2rpYsx6LZCpLzblu9BIzp5Pum61yZXJ7L2cZVlX3SathIRTvPZaPyZPHsuSJTM5dCiaxMTE/17sVcrsbeqVZstq35079/LRx1/w27wfCZ47hW0RUY5sX4/7nrsrPUKNmgEcPXqMDz9497rkuJxrP4eX3rduvVbUeqApgUHt6datE7Vrp4x2vdC1B91e6sS6tb9xa/5bOHfu/PWIcVX+y7nt0+81vvx8An///Y/TtoCm9Tl+/CRbt2T87kx2ldXf4aOP1+WOqhWY8/UvTusL3VaYV0e+yRc9R1/yb9iTMv0UNYtSa6fmnJsmZ1zsCd49ypzqAAAgAElEQVRu+gZv1nmJOq3rU7CYe94kXw835Pm8itePuo/Xo/y9Ffj161muLiv7ukHnnOeUWykesCwrAsAYEwkssSzLMsZEAGWBLUCIZVlngbPGmGNAiSyOtd6yrOjUY21J3T8sbQPLssYB4wD+nTHkuv0FlyiQj6OnLr7A/XHqH8e0lQt+2biPLzrWB6Da7cU5m5hMwj9nKXJrHkebO24rSF7vXOw9lkAVv6zfUcv1FxMT6zTy6+fnQ2zssUzbxMQcxW63U6BAfuLiEi553HnzFjNv3mIAnn/+GZI88H2C6JhYSpW+OFLu51eS2CNHM7Yp5UNMTCx2u52CBQoQF5dATHTKese+pUpyJDZl34kTpzFx4jQA3hvyNtGpI7jHjl0cHfpu/A/8+stEV0VzklKr8zk8EvtHhjalS/lezFmwAHFx8an5053/Iyn7xqYe4/jxk/w6+zdq1vQnLGwdu3bto1nzZwCoWPEOmj3mPJ3EHY4cOYpfmk9BfP1KcvSo8/P2SMzRlPN2JPV5W/BW4uMSqF6jGi1aNmXQe70pWLAAycnJnDlzFh/fEjzWrCGNA+qSO09u8ue/la+++ZiXXujp7niZijt6kqI+xRzLRXyKEvdHXIZ2VR+pxhPdn2Rg236OKR4AeW/NS98J7/Ljx1PYs3m3W2q+FulzFvUpSnwmOe955F5adW/DkLb9nXJeEH8snujdh7mrVmXWz1vj0pqvxc1yPk/GnqCYr/P5jDuWMee9tavRpntb+rftm+n5lJwtp4ycn03zc3Ka5WQuvsFI2yaJrN94XGm7666KX1F+P/knMfF/cT4xiQURh6h7t/MXd3wK5WPdvpROzf5jpziXmEThW3ITE/+X4wugRxL+4tCJ0/gWyp5faLmRbdiwlQoVylG2bGm8vLx48skggoMXObUJDl5E+/Yp37B/4olmLF+++rLHLV485U1WoUIF6dq1AxMm/Hj9i7+M9Nnatm2ZabYOHZ4EoPUTzVm+fJVjfdu2LfH29qZs2dJUqFCO8PAtwMVspUv70qrVY0yfPhuAkiVvcxy3ZcumREbucnlGgPANW5xytmvbkuDghU5tgoMXXszZujnLHDkX0i5dzvXhm8mXLy+33pry95gvX14aN6rryHMhvzGGd/q+zrhxk92SM61NGyO4o3xZbi9TCi8vL55o3Zz5IUuc2vw2bwlPPZNyp4+WrZqyckXKPPnmTZ7B/576+N9Tn6++mMjIT77i23FTeG/QJ9xz96P431OfLp3eYGXo2mzTMQfYu3UPPuV8uK30beTyysUjQY+yYdF6pzZlq5Sj64hufPD8ME6fvPjl/Fxeueg1ri8rfl7G2nmX//v1pH1b91CynA/FS9+G3SsXDwXVZmMmObuMeJmPnx/ulLNIyaJ45fYG4JYCt3BXjbuJ3XeE7OhmOZ97tu7Bp5wvt5UuQS6vXNQOqkN4upzlqtxBtxGvMPz59zh18lQWR7pJ3KBzznPKyPm1+hPINt88zGW30SewBt0mLSU52aLl/eWpUKIQXyzZSmXfotSrVIoeTaszZPZapq7eCcYw+ImHMMaw+dAxxodGkctuw2agb2BNCt+S5/K/NBvqNfB9wjdvIyHhNA1btefl5zvQOih738LrgqSkJN54413mzp2M3W5n0qTp7NixmwEDerBxYwQhIYuYOHE648ePIjIylLi4BJ57rrtj/127VpE/f368vb0ICmpCYGB7du7cwyefDKJq1coADB8+ir17D3gsW0jwVGx2G5MmTidqx24GDujJxk1bCQ5exIQJ05g44TOiosKIj0ugfYeU71tH7djNzJlz2bp1KUmJSbz+en/HPOTp08ZRtGhhzp9P5LXX+5GQkPJiMmJ4P6pVq4JlWRw6dJiXX+njtpyvv9GfkJAfsNtsTJw0naio3Qwc2JONG1Nyjp8wjYkTR7MjKoz4+ASebZ+aM2o3P82cy7aty0hMSuK11/uRnJxMiRLFmfnTdwDYc9mZNu1XFi5cDsBT7VrxUrdOAPz66zwmTprulpzpM/fuOZiZv47HbrMzdfJMdu7cS99+r7N5cwTz5y1lyvc/8dU3H7Nhy2Li4xPo0vlNt9d5PSUnJfPdgHH0+34QNruNZTOWEL3nMO16PMO+bXvZsHg9Hd7pTJ58eXnri94AnDhygg+6DOOhwEeoVKsK+Qvlp36blFt8ju05moNR7v+7vJzkpGQmDviGvt8PxGa3s3zGYqL3HKZNj6c5sG0vGxeH88w7nciTLw+vp+Y8eeQ4H3cZjl+FUrTv3zl1apoheNxsDu865OFEmbuZzuc3737FwMmDsdltLJm+mMO7f+fpHs+yN2IP4YvW07FfZ/Lky0OvL1OumcePHGfE8yl3QBs28338ypcizy15+GbdBMb2Gs2W0M2ejCTXwGTXeVcXGGPKAsGWZd2TujwxdXnmhW3ATOAvy7I+Tm2zHQi0LOugMeYHUuaq/waEAD0tywpMbfc5sMGyrIlZ/f7rOa0lO8vVoL2nS3Cb/KXqeboEl0v24Dt+d8ru16/rJX/ufJdvdANoWKSyp0twi1w5+G5bVyMxq8nvN5jEm+R6C/DL73Oz1ZP331/ed+mTLO/jfTySN9uPnFuWdRC4J81yp6y2pVmftv0z6TYvT7OtOyIiIiKS89ygb4xyypxzEREREZEbXrYfORcRERERySAb/h8L14NGzkVEREREsgmNnIuIiIhIzqORcxERERERcSWNnIuIiIhIznOD3k5XI+ciIiIiItmERs5FREREJOfRnHMREREREXEljZyLiIiISM6jkXMREREREXEljZyLiIiISM5jaeRcRERERERcSCPnIiIiIpLzaM65iIiIiIi4kjrnIiIiIpLzWJZrH1fAGNPUGLPLGLPXGNMnk+23G2OWGWM2G2O2GWOaXe6Y6pyLiIiIiFwlY4wdGAs8BlQGnjbGVE7XrD8ww7Ks+4CngC8ud1zNORcRERGRnMfzc85rAXsty9oPYIyZBrQEotK0sYACqT8XBI5c7qDqnF9GwQ7jPF2CW/wd097TJbjNn9HLPV2CW1St3M7TJbjcw/nKeLoEt5h5fJOnS3CL345v83QJbmEzxtMluMW5pERPl+AWSclJni5BXMQY0xXommbVOMuy0nYM/YDDaZajgQfSHWYQsNAY8ypwC9Docr9XnXMBIH+pep4uwS1ulo65iIjIDc/FI+epHfFLjdJm9k47/WT1p4GJlmV9Yox5CJhsjLnHsrK+Sbs65yIiIiKS83j+PyGKBkqnWS5FxmkrzwNNASzLWmOMyQMUA45ldVB9IVRERERE5OqFAxWNMeWMMd6kfOFzTro2vwMNAYwxlYA8wPFLHVQj5yIiIiKS41jJV3a7Q5f9fstKNMZ0BxYAdmC8ZVmRxpghwAbLsuYAbwHfGGPeJGXKSyfLuvR9GtU5FxERERG5BpZlzQPmpVs3IM3PUcAjV3NMdc5FREREJOfx/K0UXUJzzkVEREREsgmNnIuIiIhIzuP5u7W4hEbORURERESyCY2ci4iIiEjO4+G7tbiKRs5FRERERLIJjZyLiIiISM6ju7WIiIiIiIgraeRcRERERHIejZyLiIiIiIgraeRcRERERHIeS3drERERERERF9LIuYiIiIjkPJpzLiIiIiIirqSRcxERERHJefQ/hMq1Cgiox/aIFURFhdGr5ysZtnt7ezN1yhdERYURtnIuZcqUAqBIkUIsXDCDuJO7GDVqqNM+Qwb3Zt/e9cSd3OWWDFeiceO6bNu2jMjIUHr2fDnDdm9vbyZPHktkZCihobOdci5YMI0TJ3YwcuQQp33atAkiPHwBmzYtZtiwd9yS43rpP/xT6jR/ilbtX/J0KddV7foP8dvqmSxYN4sXXu2YYXuNB+/j58WT2X5kDU0CG3igwmt3T11/hi/5jBHLx9CsW6sM2wOeD2ToopEM/u0Tek4dSFG/Yo5t3+6bzqB5HzFo3ke8+s3b7iz7ijRqXIeNmxezZdtS3nwr43PS29ubCZNGs2XbUpYun8Xtt/sBUL36vYStCSZsTTCr1oYQGBTg2CciKpQ1638jbE0wy1fOdluWS2nUuA6btixha8QyemSRc9L3Y9gasYxlK35x5KzfoDYrV81h3frfWLlqDnXrPuTYp3Xr5qxd9xvhGxbw3tA+bstyKdf7fObO7c2yFb+wam0I68Ln806/N9yaJyuueF3x8vJi7Nj3iYhYztatS2nV6jG3ZEkvIKAe27eHsiMqjF69sugbTP2SHVFhrAq72DcA6N27Ozuiwti+PZTGjes61hcsWIBp08YREbGCbduW8+AD1QEYNKgXmzYuYkP4QuaF/ICPTwnXB5Rr5rHOuTGmrDFm+1W0n2iMaZP687fGmMqZtOlkjPn8etb5X9lsNj77bChBLTpQrVp92rVrSaW7Kzq16dz5KeITTlG5cm1Gj/6G4amd0DNnzjJo8Ee83ee9DMcNDlnMI7UD3ZLhSlzI2bJlR/z9G9K2bQvuTpezU6d2JCScokqVOowZ8y1Dh/YFUnIOHvwJffoMc2pfpEghRox4h8cee5r7729EiRLFqF//Ebdl+q9aNWvMV58OvXzDHMRmszHgg9688PTrBNZuS/MnAih/ZzmnNrExR+n72mCCZy3wUJXXxthstB/ShZGdhtG/8Zs80KI2vhVKObX5PeoAQ4LeZuBjb7HhtzU82beDY9u5M+cY1KwXg5r1YswLH7i7/Euy2Wx88ulgWj/emZrVm9DmySDuuruCU5vnOrYlIeE0/vc2YOzn4xn8XsobjKio3dSt3ZLaDwXyRKtOfDZmKHa73bFf88eeofZDgdR7tKVbM2XGZrPx6cghPNGqEzXuD+DJJ1twd7qcHTu1JSHhFNWq1mfsmO8cne2TJ+N4sk0XHqj1GC++0JNvvvsUSLkODR3el8Dmz1KzRhNuu60Y9eo97PZsabnifJ49e47AZs/yyIPNeeShQBo1rkPNmv6eiOfgitcVgD59XuX48RNUrVoPf/+GrFy51i150rLZbIz+bBhBQe25t1p9nmrXikqVnLP9r/PTJMSfolLl2nw2+huGD+8HQKVKFWnXtiXV/BsQGPgsY0YPx2ZL6c6N/HQICxcso2rVulSv3pgdO/cA8MknX3J/9cbUqBnAvHmL6d/vTfcGdhUr2bUPD8mRI+eWZXWxLCvK03VciZo1/dm37yAHDvzO+fPnmTFjNkFpRp4AgoICmDz5JwB+nhVC/fq1Afjnn39ZvTqcM2fOZjju+vWbOHr0mOsDXKH0OX/6aW6mOadMmQnArFnzHB3tCznPnj3j1L5cudvZs+cAJ07EAbB0aZjHRjiuRQ3/qhQskN/TZVxX995fhd8PHCb6UAznzycy75dFNGxa16lNzOFYdkftxcphHzfe4V+BY4eOcvzwMZLOJ7Ju7ir8A2o6tdm5JpJzZ84BsH/zHgqXLOqJUq9ajRrV2L//EAcPHub8+fP8PDOY5oGNndo0D2zEj1N/BuDXX35zdED//fcMSUlJAOTJnTtb37msRo1q7N93MefMmXMz5mzemKlTUnL+kibntq1RHI1NuaZGRe0md+7ceHt7U7bc7exNcx1atmwVLVs1dWOqjFx1Pv/++x8AvLxykcsrF5aHT7YrXlcAOnZsy4cfjgXAsixOnox3cZKMatW8zynb9BmzCQpq4tTGqW/wcwgNUvsGQUFNmD5jNufOnePgwcPs23eQWjXvI3/+W6ld+wHGT/gRgPPnz3Pq1GkA/vzzL8dx892Sz+Pn9rpJtlz78BBPd87txphvjDGRxpiFxpi8xhh/Y8xaY8w2Y8wvxpjC6Xcyxiw3xtRI/bmzMWa3MWYF8EiaNkHGmHXGmM3GmMXGmBLGGJsxZo8xpnhqG5sxZq8xplj633G9+Pn6EH041rEcE3MUXz+fdG1KEh2d0iYpKYlTp09TtGiG2Nmar29JoqOPOJZjYmLx9S2RZZukpCROn/7zkjn37TvEnXeWp0yZUtjtdoKCAihVytc1AeSKlChZnNiYPxzLR2P/oIRPcQ9WdP0UKlGEuCMnHMvxsScpXKJIlu0fbduAiOWbHcteub0ZMOcD+v0ynPvSdeo9zSfNNQbgSEwsvuk+1vbxLeF0HTp9+k+KpP591qhRjXXh81mz/jfeeK2/o3NnWRa/zpnEirDZdOr8lJvSZM3XtyTRMemut74l07Up4WiTcr3NeB1q1eoxtm2N5Ny5c+zfd5A77yrP7bf7pV6HGuPn4euQq86nzWYjbE0w+w6Gs2zpKjZs2OqmRJlzxetKwYIFABg4sCdr1oQwdeqX3Haby7oAWfL1y5jNL/1z1a8kh9NkO3UqpW/gl9m/i19J7rijDCdOnOS7b0cSvn4BX3/1Efny5XW0GzLkbfbvC+fppx9n0OCPXJxQ/gtPd84rAmMty6oCJACtge+Bty3LuheIAAZmtbMxxgcYTEqnvDGQdqpLGPCgZVn3AdOA3pZlJQNTgGdT2zQCtlqWdSLNfhhjuhpjNhhjNiQn/f2fAhqTcV36d6wmk0Y57V3tlWS42pwJCad47bV+TJ48liVLZnLoUDSJiYn/vVi5djfAczUrV/P8fLDVo5S9tzzzx12cZ93r4ZcY0uJtxr02iqcHdKb47dlnTucVXYfItBEAGzZs5YGaTalXpxVv9exG7tzeAAQ0fJI6j7Sg9eP/44UXO/DwI559U3I9rkOVKlVkyNC3ee3VlCkECQmneeP1d5k0+XMWLp7BoUMxJHn4OuSq85mcnEzthwKpdOfDVK9+L5Uq33nda78arnhdyZXLTqlSvqxZs4GHHmrOunUbef/9/v+92Kt07dmy3jeX3c5991Xl66+/p2atJvz99z/07t3d0WbAgA+4o3xNfvzxF15+ufN1SOF5VnKySx+e4unO+QHLsrak/rwRKA8UsixrReq6SUCdS+z/ALDcsqzjlmWdA6an2VYKWGCMiQB6AVVS148Hnkv9+X/AhPQHtSxrnGVZNSzLqmGz33ItuRyiY2IpVfriSLmfX0lijxzN2KZUShu73U7BAgWIi0v4T7/X3WJiYp1Gtf38fIiNPZZlG7vdToEC+S+bc968xdSp05J69R5nz5797N178LrXLlfuj9hj+Phd7HSW9CnBsaMnLrFHzhF/9CRFfC+OoBX2KUrCsYwfd1d+pCqB3Vszusv7JJ672Em70Pb44WPsXBvJ7VXKZdjXU47EHHVcYwB8/XyITTct7siRo07Xocz+Pnfv2sfff/9D5cp3ATim1p04fpLgOQupXqOaK2NcVkxMLKX80l1vY/9I1+aoo03K9fZiTl+/kvww7Wu6dnmLAwd+d+zz27wl1K/7OA3rt84W1yFXnc8LTp36k7CV62jU+FIvv67niteVkyfj+fvvf5g9ez4As2aF4O9/jwuqv7SY6IzZjqR/rkbHUjpNtoIFCxAXF5/aZ0j373LkD6JjYomOjmV9eMonej/PCuE+/6oZfve0ab/w+OPNXBFLrhNPd87TTqZOAgpdwzGyeos8BvjcsqyqwItAHgDLsg4DfxhjGpDSuf/tGn7nFduwYSsVKpSjbNnSeHl50bZtS4KDFzm1CQ5eRIcOTwLQ+onmLF++ypUluUT6nE8+GZRpzvbt2wDwxBPNWL589WWPW7x4ypzeQoUK0rVrByakzqUTz4jYHEWZO27H73ZfvLxy0ezxxixdEOrpsq6LA1v3UqKsD8VK3YbdKxcPBD3ClkXhTm1ur1KO54a/yOgu7/PnydOO9fkK3EIu75Q7095aOD8Vq99N7J5ot9Z/KRs3buOO8mUpU6YUXl5etG4TyLyQxU5t5oUs4elnWwPQ6vHHWLFiDYBjWhlA6dK+VLzzDg79Hk2+fHm59daUwYt8+fLSoGFtdkTtdmOqjDZu3Eb5ChdztmkTlDHnvMU82z4l5+NpchYsmJ+ffx7PoAEfsnbtRqd9Ll6HCvBC1/ZMmjgdT3LF+SxarAgFC6Z8RyZPntzUq/8Ie3btd2OqjFz1uhISsthxN5769R9hx44917/4ywjfsMUpW7u2LQkOXujUJjh44cW+QevmLEvtGwQHL6Rd25Yp34koW5oKFcqxPnwzf/xxnOjoI9x5Z3kAGjSozY4dKX+TFSpcHCwICgxg16597ojpejfonPPsdp/zU0C8MeZRy7JWAh2AFZdovw74zBhTFDgNPAlcmCRXEIhJ/Tn9/d6+JWV6y2TLspKuV/GZSUpK4o033iUkeCo2u41JE6cTtWM3Awf0ZOOmrQQHL2LChGlMnPAZUVFhxMcl0L7DxdtF7d61hgIF8uPt7UWLoCY0b/4MO3buYcTwfrRr14p8+fKyf184Eyb8yHtDP3VllCvKOXfuZOx2O5MmTWfHjt0MGNCDjRsjCAlZxMSJ0xk/fhSRkaHExSXw3HMXP27btWsV+fOn5AwKakJgYHt27tzDJ58MomrVlNlKw4ePYu/eA56KeNV6DXyf8M3bSEg4TcNW7Xn5+Q60TveFn5wmKSmJ9/p8yHfTR2Oz2/n5hzns3bWfV99+ke1bdrBsQSj3+Ffm84kfUqBgAeoH1KZ77xcJqtPO06VfVnJSMlMGfEuP7/tjs9sIm7GUI3uiafVmOw5G7GPL4g207duB3Pny8PIXbwFwMuYEY174AJ8Kpeg4vCuWZWGMYd6Xv3Bkb/bpnCclJdHrrUH8MnsSdruNyd//xM4de+jX/w02bYrgt3lL+H7SdMZ9+ylbti0lPv4UnTu+BsBDD9fgzR4vcT4xkeTkZHq8MYC4k/GULVuaqdO+AiCX3c5PM+aweJFn36glJSXxVo+B/Drne0fOHTv20P/dN9m0KYJ5IYuZNHE63343kq0Ry4iPP0Wn514F4MWXOnJH+TK83fdV3u6bsq5l0HMcP36SDz8aQNWqlQB4f8Roj1+HXHE+q9xzN1+N+wi73Y7NZvjl53nMn7/U4zld8brSv/8Ixo8fxUcfDeTEiTi6dn3LI9lef6M/ISE/YLfZmDhpOlFRuxk4sCcbN6b0DcZPmMbEiaPZERVGfHwCz7ZP6RtERe3mp5lz2bZ1GYlJSbz2ej+SU6dgvPHmu3w/aQze3l7sP/A7Xbr0AGDYsL7ceWd5rORkDv0ewyuvZI9bgkrmjKfmixpjygLBlmXdk7rcE7gV+BX4CsgH7Ac6W5YVb4yZmNp+pjFmOdDTsqwNxpjOQF8gFtgC2C3L6m6MaQmMJKWDvhaoaVlWvdTf5QWcBGpZlrXzUnV65y51Y0yovQyb8fSHKO7xZ/RyT5fgNlUrZ/8O8X/1cL4yni7BLWYe3+TpEtwi+Qb5/sLl2DKbNH4DOpd0c3xHKCnZpWN82cr5czHZ6sn799D2Lr1o3NJ/ikfyemzk3LKsg8A9aZY/TrP5wUzad0rzc700P08g83njs4Gs/leMaqR8EfSSHXMREREREXfKbtNaXM4Y0wfoxsU7toiIiIhITpPD/j+NK3VzzGVIw7Ks9y3LKmNZVpinaxERERERSeumGzkXERERkRuAB+9F7ko33ci5iIiIiEh2pZFzEREREcl5NOdcRERERERcSSPnIiIiIpLzWJpzLiIiIiIiLqSRcxERERHJeTTnXEREREREXEkj5yIiIiKS41i6z7mIiIiIiLiSRs5FREREJOe5Qeecq3MuIiIiIjnPDdo517QWEREREZFsQiPnIiIiIpLz6D8hEhERERERV9LIuYiIiIjkPDfonHN1zi8j2boxT3xGN+ZHQzeziKjpni7BLYqVbezpElzuZrkOnUk85+kS3MJ4ugA3KZT3Vk+X4Banz/7j6RLkBqPOudxUqlZu5+kS3OJm6ZiLiMjNy7pBR84151xEREREJJvQyLmIiIiI5DwaORcREREREVfSyLmIiIiI5DzJN+bNLDRyLiIiIiKSTWjkXERERERyHs05FxERERERV9LIuYiIiIjkPBo5FxERERERV9LIuYiIiIjkOJalkXMREREREXEhjZyLiIiISM6jOeciIiIiIuJKGjkXERERkZxHI+ciIiIiIuJKGjkXERERkRzHukFHztU5FxEREZGc5wbtnGtai4iIiIhINqHOuYs0CahH5PZQdkaF0bvXKxm2e3t788PUL9kZFcbqsLmUKVPKse3t3t3ZGRVG5PZQAhrXBSB37tysWRXMxg2L2LplKQMHvOVo/3K3TuyMCiPxXAxFixZ2fbhUAQH12B6xgqioMHr1zDzj1ClfEBUVRthK54y9e71CVFQY2yNW0Dg1I0D37s+zedNitmxewquvPu9Y/27/HhzYv4Hw9QsIX7+Apk0buDbcNahd/yF+Wz2TBetm8cKrHTNsr/Hgffy8eDLbj6yhSWD2q/9a9R/+KXWaP0Wr9i95upRr0rBRHTZsWsTmrUt5s8eLGbZ7e3szYdJoNm9dypJlP3P77X4A3F/9XlaunsvK1XMJWxNMYFCAY5+CBfPz/ZTPCd+0kPUbF1Cz1n1uy5OVRo3rsGnLErZGLKPHWxnPlbe3N5O+H8PWiGUsW/GLI2f1GtVYvTaE1WtDWLN2HkEtLub84qsPOHAwnPXh892W44LrfY291DGzusa+1eMlNoQvZEP4QrZsXsLZf3+ncOFCLkqces3dHsqOqDB6ZZF56tQv2REVxqp0mXv37s6OqDC2bw91XHPvvLO8o/4N4Qs5eWInr73aBYB33+3BwQMbHNs8dc1t0PBR1myYz/rNC3ntzRcybPf29uKbCSNZv3kh85fMoHTq87b07X78fnQry1b+yrKVv/LRyMEA5M2bhx9mfM3q8N9YuTaYdwe9leGYnhDQuB4R25YTFbmSnj1fzrDd29ubKZO/ICpyJStD5zjObZEihViwYDonT+xk1Mj3Mj32zzPHs2njYpfW7zHJLn54SI7onBtjlhtjalymTSdjzOfuqulSbDYboz8bRmBQe6pWq0+7dq2oVKmiU5v/dX6a+PhT3F25NqNGf8OI4f0AqDgs4ssAACAASURBVFSpIm3btuRe/wY0D3yWMaOHY7PZOHv2LI0C2lK9RmOq1wigSUA9Hqh1PwCr14TT5LGnOHjwsFszfvbZUIJadKBatfq0a9eSSnc7Z+zc+SniE05RuXJtRo/+huHD3knJeHdKRn//BgQG/Z+9+w6PovoaOP69uyQUCSBFSEJvKig1ofcSShIIXQUVG5ZX6fBD6YpYAQVRBKQjvYfQW6gaCDWBUAOkUSQBlRY29/1jlyWbAqHsboLn8zz7sDNzZvYednbm7tk7k26MH/8lBoOBihWe5523X6VOXT+qe/nQunUzypYtZd3e+AlT8K7RAu8aLVi7drPDcs0Ig8HAsG8G8t6rvfCr1xnf9j6UKV/KJiY2Oo5Pe44kcOk6J7XSPgJaN2fS2FHObsYjMRgMjBk7go7t36aGVws6dPLn+RfK2sS88WYnEhKuUrVyE36eOJ2RX/wPgKPhx2lUP4D6dfzpEPAWP4wfhdFoBODrb4excUMw3tV8qFvLj+MRJx2eW3IGg4Gx4z6nfUB3vKr50KlTG15Ikeeb3TuTkHCVyi83ZuKE3/hi1CAAwsMiqF+3DXVq+RIQ8Cbjx39pzXPu7CUEBHR3dDp2Ocbeb5vpHWPHjJ2El7cPXt4+DBnyNcHBe4iPT7Brzv7+3ahUuTGvpJNzQvxVXqxQjx/HT2F0spy7dG5L5SpN8EuW8/Hjp6ztr1GzJdev32D5ijXW7f04fop1uTOOuQaDga/HDOOVju9St4Yv7Tr4Uf75MjYxXd/oRELCNWpU9WHSzzMYNrK/dVnkmXM0rh9A4/oBDOgz3Dp/4oRp1PFuRZP67ahRsxpNmzVwWE5puXs+bdP2DSpXaUKXzm15IeX5tPsrJCQkUKFifcZPmMqXo8zn05s3bzFy5PcMGpT2Mbht25b88++/ds9BPFlZonOe1dTwrsqpU5GcOXOOxMREFi5cQRv/FjYxbfx9mD17EQBLlqymSeN6lvktWLhwBbdv3yYy8jynTkVSw9tcdfv33+sAuLhkI5uLi/XP1h44EMbZs1GOSg8Ab+8qqXL0T1Y5BPBPnuPS1TS25Ojv75MqR2/vKrzwQln++GM/N27cxGQysT14D23btnRoXo+qUrWKnDtznqiz0SQm3iFo2QaatmxoExN9Ppbj4SefugtYvKq8TN48bs5uxiOp7lWZ06fPEhl5nsTERJYuDsTXt5lNTGvfZvw+dykAy5etoWGj2gDW/RQgR47s1s+jm1tu6tb1ZtbMhQAkJiZy9erfjkopTV5elTl96l6eixevwtevuU2Mr29z5s5ZAsCyZWto1KgOkCLP7NlJ/teyd+78k/gr9umM3o89jrH322ZGjrFdurRl/oLldsjWLGX7FixcgX+KnP3TydnfvwUL0jmv3NWkST1Onz7LuXPRdsvhYVWrXonI02c5GxlFYmIiy5euppVvU5uYVq2bsOD3ZQCsWr6O+g1r33ebN27cZOf2PwDzZ/PQwXDcPQvbJ4EMSnU+XbQy7fPpnMUALF26msaN6wJw/foNdu0K4eatW6m2+8wzuejV6z2++mq8/ZNwEp2k7fpwFrt0zpVSA5VSPS3PxymlNlueN1VKzVFK+SildiulQpVSi5RSuS3Lqyultiml9iml1iml3FNs16CUmqmUGmWZfkspdVwptQ2omyzOXyn1h1Jqv1Jqo1KqsGXdE0qpQsm2dVIpVfBJ5+/hWYTzUTHW6ajoWDw8iqQbYzKZuHr1GgUKPIuHRxrreprXNRgM7A1ZT2z0ITZtCubPkP1PuukZ5unhTtT5WOt0dHQcHp7uKWKKEBVljjGZTFy9ZsnR0906HyA6Kg5PD3fCwiOoX78m+fPnI2fOHLRs2YSiRT2scR9+0J19ezcw+dfvyZcvr50zfDiFixQiNvqCdTou9gKF3Qs5sUUiIzw8ChMdZbsfu3vYnqjdPYpYY0wmE9eu/k1+y9CG6l6V2ROyhl1/BNGn11BMJhMlSxbj8uUr/DzpW7bvXMmEn0aTK1dOxyWVBg+PIkRFp/i8pjwmeRS2xpg/r39bh3B4eVchZO86/ghZS69eg62ddWexxzE2I9tMT86cOWjh04ily4IeJ6378vAsQlSy9kVHx+KZwZzNx2Lbde+eV+7q0rktC1J8ufjow7cI3beBKZPHOOWY6+5RmOjoOOt0TPQF3N1tP59F3AsTnWy/vXbtb/LnN++3xUsUZfP2ZaxYPZtataun2n6evG74tGrM9m277ZjFg6XcJ9N8b5O9h3fzfNAw1hHDB/DDD1O4cePGk2+0sCt7Vc6DgfqW515AbqWUC1APOAwMAZpprasBe4G+luUTgI5a6+rANODLZNvMBswFjmuth1g67iMxd8qbAxWSxe4AammtqwLzgYFa6yRgDtDVEtMMOKi1vvxkUwelVKp5WusMxNx/3aSkJLy8fShRygtvr6pUrPj8E2rxw0ujmRnMUae77rFjJ/nu+59ZEzSPwFVzOHQ4nDt37gDw6+RZvPBiXby8fYiLu8i33wx9Ink8MRl4z0Xmk97n0DYm9Xp339t9ew9Sy7sVjRu2o2+/D8ie3ZVs2bJRuUpFfps6l/p12/Dv9Rv0SWOMtyM9+jHJHLM35ADeXi1oWL8t/fp/RPbsrvZpaAbZ4xibkW2mx8/Ph12799ptSAvY77wC4OLigp+fD4uXBFrn/frrLJ5/oQ7VvXyIjbvId98Oe5zmP5LH2W8vxF2kasXGNKnfjqGDv2bS1DHkdnvGGmM0Gpn821imTprN2UjH/vKcUsbyTL3e/fbPSpUqUKZMCVaudPz1IA6VpO37cBJ7dc73AdWVUm7ALWA35k56feAG5o70TqXUAeBNoATwPPASsMEyfwhQNNk2fwWOaK3vdthrAlu11pe01reBBcliiwLrlFKHgQFARcv8acAbludvA9PTarxSqodSaq9Sam9S0sOP1YqOiqVYsopvUU93YmMvpBtjNBrJmzcPV67EEx2dxroxtutevXqNbcG7aOHT6KHb9qRERcdStNi9SrmnZxFiY+JSxxQ1xxiNRvLmycOVKwlER92bD+BZtAgxseZ1Z8yYT81arWjarCPxVxI4efIMABcvXiYpKQmtNb9N+x1v7yr2TvGhXIi9aPPTaBH3wlyMe+Lf+8QTFh0dh2dR2/04LsVnNSZZjNFoJE9et1RDOY5HnOLf6zeoUOF5oqNjiY6OY9/egwCsWL6GypUr4kzR0bEU9UzxeU15TIqOs8aYP69uXEmRZ0TEKa7/e50KTiwMgH2OsRnZZnq6dG5j1yEtgOW4ea99np7uxGQwZ/Ox2Hbd5OeVli0bs3//YS5evHfMsjnm/jYXLyccc2Oi4/BMVuH38CxMXNxFm5jYmDg8k+23efK4ER+fwO3bidYvS4cOhBF55hxlkl3DNPbHLzh9KpJff5npgEzuL+U+meZ7Gx1nfQ/v5pny85lcrZrVqVq1EhERu9i8aSnlypVi/fqF9klAPHF26ZxrrROBSOAtYBewHWgMlAHOABu01lUsjwpa63cABYQlm/+y1jr5oKtdQGOlVI7kL5VOEyYAP2mtXwbeB3JY2nUeuKCUaoK5c78mrZW11pO11l5aay+D4Zm0Qu4rZO8BypYtRcmSxXBxcaFz57asClxvE7MqcD2vv94JgA4dfNmydad1fufObXF1daVkyWKULVuKP0P2U7BgfvLmzQNAjhw5aNqkPhERpx66bU/K3r0HU+UYGLjBJiYwcMO9HNv7stWSY2DghlQ5hoQcAKBQoQIAFCvmQUBAKxYsWAFAkSLPWbfbtm1LwsIi7J7jwzi8P5wSpYvjWdwDF5dstG7XnM3rgp3dLPEAofsOUaZMSUqUKIqLiwvtO/oRFLTJJiYoaBOvdW0PQEC7VgRbfgIvUaKo9cLIYsU8KFeuFGfPRXHx4mWio2MpW87cEWjYqA4Rx5x7Qei+fYcoU/Zenh07+hO02vbuDUFBG+narQMA7dq1YluaeXpSrnxpzjn4GpeU7HGMzcg205InjxsN6tdi5Ur7Xuidsn1dOrclMEX7AtPJOTBwPV3SyPmuLl0CUg1pSX7MDWjbyinH3P2hhylVpiTFLfttQHtf1gbZXpi6NmgzXV5rB4B/QAt2BO8BoECBZzEYzF2cEiWLUrpMSc5aLuj9dEhv8uTNzeBBox2YTfrM59OS9/a9Tm3SPp926whA+2Tn0/RMnjKbUqW9eP75OjRp2p4TJ87g49PZbjk4zVN6txZ7/hGiYKA/5gr1YWAs5or6HmCiUqqs1vqkUioX5kp3BFBIKVVba73bMsylvNY6zLK934AGwCKlVDvgD+BHpVQB4BrQCThoic0L3L2qJeU97aZiHt4yW2ttl4GTJpOJXr2HELT6d4wGAzNmLiA8/Dgjhvdn776DBAZuYNr0+cycMZ5j4TuIj0/gtW7mWyeFhx9n8eJVHD64hTsmEz17DSYpKQl398JM++0HjEbzXQUWL17F6iDzyfXj/3ub/v0+okiRQuzft5E1azfz/gcD7JGaTY69ew9ldeBcDEYDM2csIPzocYYP68++UHOO06fPZ8b0HwkP30H8lQS6vW7J8ag5x4MHN2O6Y6JXryEkJZk/BQvmT6ZAgWdJTLxDz16DSUi4CsBXowdTuXJFtNacPXuej/5vkF3ze1gmk4kvBn3LbwvGYzAaWfL7Sk5GnOaT/73PkQNH2bIumJeqVOCnGd+SJ28eGvvU4+OB7+PfoIuzm/7YBgz/mpD9h0hIuEbTgG589M7rdEhxoVpmZTKZ6N9vJEuXz8BoNDBn9mKOHT3BZ0N6sz/0MGuCNjF75kImTx3D/oObiY9P4O3uvQCoVduLPv3eJzHxDjopiX59hnPlr3gABvYbydTfxuHi6kLkmfP834cDnZkmJpOJfn2Hs3zlLIxGA7NnLeLo0RMMGdqH0NDDBK3eyMwZC5j62zgOHt5CfPxVur/xCQC163jTr98HJN65Q1JSEn16D+UvS57TZ/xI/Qa1KFDgWSJO7OLLUT9YL4S1dz5P+hgLpLlNuP8xNqBtKzZsDOb6dfuO672b8+oU7Rs+vD/7kuU8Y8Z4jlpy7pos50WLV3EojZxz5sxBs6YN+Oij/9m83tdfDaFy5QporYk8G5VquSOYTCY+7f85C5dOxWA0Mm/OEiKOneR/n/XkwP4jrFuzmbmzF/Pz5O/4c/964uOv0uPtPgDUruvN/z7ryZ07JpKSTPTvM5yE+Ku4exSm74APOR5xis3B5gtJf5syhzmzFjs8v+R59u49lMBVczAajcyYuYCjR48zbFg/QvcdInD1BqbPmM/0aT8QHradK1cSeP2Ne7fSjIjYRR43N1xdXfD3b4GvX1eOHTvhtHzE41P2GherlGoKrAXyaa3/VUodByZprcdaKtffANkt4UO01iuVUlWA8Zg719mAH7TWU5RSW4H+Wuu9SqmRQHnMY8ffBD4FYoEDgFFr/bFSqi0wDnMHfQ/grbVuZGmXC/AXUENrfexBeWRz9fxPDBw2pDWg7SlUOq/7g4OeAofDFzw46ClRsGTzBwdlcaYkJ5ZwHOjmndvOboJD/DeOtpAvZ25nN8Ehrt267uwmOMytm+cz1e4b36mRXftozy7a6pR87VY511pvAlySTZdP9nwz4J3GOgcwV8dTzm+U7PnwZIumk8a4ca31CmBFOk2rjPlC0Ad2zIUQQgghhHAkew5ryXSUUoOAD7l3xxYhhBBCCJEVPaU/Kv6n/giR1vprrXUJrfUOZ7dFCCGEEEKIlP5TlXMhhBBCCPF0eNr+4vZd/6nKuRBCCCGEEJmZVM6FEEIIIUTWI2POhRBCCCGEEPYklXMhhBBCCJHlaKmcCyGEEEIIIexJKudCCCGEECLreUor59I5F0IIIYQQWY4MaxFCCCGEEELYlVTOhRBCCCFE1iOVcyGEEEIIIYQ9SeVcCCGEEEJkOTLmXAghhBBCCGFXUjkXQgghhBBZjlTOhRBCCCGEEFZKqZZKqQil1Eml1KB0YjorpcKVUmFKqd8ftE2pnAshhBBCiCzH2ZVzpZQRmAg0B6KAEKXUSq11eLKYcsCnQF2tdbxS6rkHbVcq50IIIYQQQjy8GsBJrfVprfVtYD7QNkXMe8BErXU8gNb64oM2KpXzBzAa/hvfX5KSntKBWynUyVXC2U0QT9jlyA3OboJDFCvr6+wm2F1OF1dnN0E8QdcTbzm7CQ6hUM5uwn+Xtu//vVKqB9Aj2azJWuvJyaY9gfPJpqOAmik2U96yrZ2AERihtV57v9eVzrkQT6GCJZs7uwkO8V/pmAshhHA8S0d88n1C0vp2oFNMZwPKAY2AosB2pdRLWuuE9DYqnXMhhBBCCJHlOHvMOeZKebFk00WBmDRi9mitE4EzSqkIzJ31kPQ2+t8YsyGEEEIIIcSTFQKUU0qVUkq5Aq8AK1PELAcaAyilCmIe5nL6fhuVyrkQQgghhMhydJJzx/trre8opT4G1mEeTz5Nax2mlPoc2Ku1XmlZ5qOUCgdMwACt9V/32650zoUQQgghhHgEWusgICjFvGHJnmugr+WRIdI5F0IIIYQQWU4mGHNuFzLmXAghhBBCiExCKudCCCGEECLL0Xa+z7mzSOVcCCGEEEKITEIq50IIIYQQIst5WsecS+dcCCGEEEJkOc6+laK9yLAWIYQQQgghMgmpnAshhBBCiCxHa2e3wD6kci6EEEIIIUQmIZVzIYQQQgiR5ciYcyGEEEIIIYRdSeVcCCGEEEJkOVI5F0IIIYQQQtiVVM6FEEIIIUSWI3drEY/Mp3kjDh/aSnjYdvr3/yjVcldXV+bM/pnwsO1sD15JiRJFAcifPx/r1i3gr8vH+GHcF9b4nDlzsHzZDA4d3ML+0I2M+mKQw3JJzsenEUeOBHM0fAcDBvxfquWurq7MnfsLR8N3sHPHKmteAAMHfszR8B0cORJM8+YNrfNPHN/D/tCN7A1Zz57dQdb5lSpVYHvwSvaHbmTZshm4ueW2b3IZ9FLDKoze9CNfbZ1A6w8DUi33ecePURvGMXLNGPrPHU4Bz4LWZVNPLWBE0HeMCPqOT6b8z5HNzpCmzRqwN3QD+w9upk/f91Mtd3V1ZfrM8ew/uJlNW5ZQvLgnANWqV2L7rlVs37WKHbsD8fP3sa6TN68bs+b8REjoev7ctw7vGlUdls/jGjJ6LA18XyGg2wfObsojady0HjtCgtgdupaPe7+barmrqwu/ThvL7tC1BG2cT7HiHtZlL1YsT+D6eWzbvYotO1eQPbsrAIOG9GLfkc2citrrsDwepEnT+uzeu5Y/96+nZ5/3Ui13dXVhyvRx/Ll/PWs3LaSYZb8tVtyTc3EH2bJ9OVu2L+e7cSOt6yxYMpUtO1awfU8g340bicHg/FPnk84zZ84c/L7wV3aFrGH7nkCGjujn0HzS07x5Q/Yf2MShw1vp1+/DVMtdXV2ZOesnDh3eytZtyyle3HyeadKkHjt2ruLPP9eyY+cqGjasnWrdhYumEBKyzu45ZETz5g05dGgLYWHB6fYTZs+eSFhYMMHBK1L0E+Zz+fJRxo373Gadjh39CQlZR2joRr788jOH5CGeDIcdYZRSkUqpgmnM32Xv13Amg8HAjz+Ook3bN6hcpQldOrflhRfK2cS81f0VEhISqFCxPuMnTOXLUeYP0c2btxg58nsGDRqVarvjfviVSpUbU6NmK2rX8aaFTyNHpGNlMBgY/+OX+Pt3o1LlxrzSJYAXX7TN6+23XiUh/iovVqjHj+OnMHr0YABefLEcXTq3pXKVJvj5dWXC+NE2J7tmzTvh5e1DrdqtrfN+nfQdnw0eTdVqzVixfE2aB2lHUwYD3T5/l3Hdv2RI8z7UbFMPj7JFbWLOhZ/hc///MbxVP/au2U2nT1+3Lrt98zYjWg9gROsBTHjvG0c3/74MBgNjxo6gY/u3qeHVgg6d/Hn+hbI2MW+82YmEhKtUrdyEnydOZ+QX5i8YR8OP06h+APXr+NMh4C1+GD8Ko9EIwNffDmPjhmC8q/lQt5YfxyNOOjy3RxXQujmTxqb+LGYFBoOBr74fymsde9Cgpj/tOvpS/vkyNjGvvd6RhISr1K7Wkl9/nsWQEf0BMBqNTJz8LQP7jqBhbX/a+71JYuIdANav3Uqrpl0cnk96DAYDX48Zxisd36VuDV/adfBLlWfXNzqRkHCNGlV9mPTzDIaN7G9dFnnmHI3rB9C4fgAD+gy3zn+ney8a12tL/Vp+FCz4LG3atXRYTmmxV54TJ0yjjncrmtRvR42a1WjarIHDckqLwWBg7LjPaRfQnerVmtOpUxteSHEcerN7ZxISrlLp5Ub8NOE3vhhlLlb99Vc8HTu+Q40aLenxXj+m/jbOZr02bVvw7z/XHZbL/dztJ7Rt+yZVqjSlc+c2qfoJ3bt3ISHhKhUrNmDChKmMGvUpcLefMIZBg760ic+fPx9fffUZrVq9SrVqzShcuCCNG9d1WE6OopOUXR/O4pDOuVLKmN4yrXUdR7TBWby9q3DqVCRnzpwjMTGRhYtW4p+skgjg7+/D7DmLAVi6dLX1A3T9+g127Qrh5q1bNvE3btxk27bdACQmJnJg/2E8i7o7IJt7anhXtclrwcIV+Pu3sInx9/dh9uxFACxZspomjetZ5rdgwcIV3L59m8jI85w6FUkN7/tXUMuXL8P27XsA2LhpO+3atb5vvCOUrlKWi2fjuHT+IqbEO/yxaidVfLxtYo7tDuP2zdsAnN5/gmeLFHBGUx9ada/KnD59lsjI8yQmJrJ0cSC+vs1sYlr7NuP3uUsBWL5sDQ0bmStTN27cxGQyAZAjR3a05XdHN7fc1K3rzayZCwHzvnv16t+OSumxeVV5mbx53JzdjEdStXolzpw+x7mzUSQmJrJ8SRAtWjexiWnRugkL560AIHDFOuo1rAVAoyZ1CT8SQfiRCADi4xNISkoCIHTvQS5euOTATO6vWvVKRJ4+y9lIS55LV9PKt6lNTKvWTVjw+zIAVi1fR/00Kqop/fP3vwBky5YNFxcXp/+Wbo88b9y4yc7tfwDmz+ahg+G4exa2TwIZ5OVVhdOn7h2HFi9ehZ+f7fnTz9eHuXOWALBsWRCNGpm7FAcPhhEXexGA8PDjZM+eHVdX8y8+zzyTi08+eZdvvpngwGzSl7KfsGjRqjT7CXOs/YSgVP2EW7du2sSXKlWcEyfOcPnyFQA2b95BQEArB2QjnoQHds6VUgOVUj0tz8cppTZbnjdVSs1RSr2qlDqslDqilPom2Xr/KKU+V0r9AdRONj+nUmqtUuq9u3GWfxsppbYqpRYrpY4ppeYqpZRlWWvLvB1KqfFKqUDL/AJKqfVKqf1KqV8Blex1liul9imlwpRSPSzz3lFKjUsW855Sauzj/Ac+iIdHEc5HxVino6Nj8fQokiomyhJjMpm4du1vChR4NkPbz5s3D76+zdiyZeeTa3QGeHjeazOkk5fnvdxNJhNXr16jQIFn8fRIva6Hp3ldrTVrgubxx541vPtOV2tMWFiE9WDVsYMfxYp64Gz5CufnSsxl63R87F88Wzh/uvH1Ozfh8Nb91mmX7K4MW/kNg5eNpmqKTr2zeXgUJjoq1jodHR2Hu4ftidrdo4g1xmQyce3q3+S37LfVvSqzJ2QNu/4Iok+voZhMJkqWLMbly1f4edK3bN+5kgk/jSZXrpyOS+o/zN39OWKi46zTsTEXcHdP8X66FyYm+t77+fe1v8mfPx+ly5ZEA/OWTGH9tiX8X893HNn0h+LuUZjoZHnGRKfOs4h7YaKT5Xnt2t/kz2/eb4uXKMrm7ctYsXo2tWpXt1lv4dKpHD21i3/++ZeVy507FMKeeQLkyeuGT6vGbLcUgZzFw6MwUdG254qUx6HkMemdPwMCWnHoYBi3b5sLJcOG9WP8+Klcv27boXUWj7TOianyfLh+wqlTZylfvgwlShTFaDTi7+9D0Uxw3nzStFZ2fThLRirnwUB9y3MvILdSygWoB5wAvgGaAFUAb6XU3YG3zwBHtNY1tdY7LPNyA6uA37XWU9J4rapAb6ACUBqoq5TKAfwKtNJa1wMKJYsfDuzQWlcFVgLFky17W2td3dLmnkqpAsB8oI2l/QBvAdMz8H/wyCzfL2zoFFWXNEJSxaTFaDQye9ZPTJw4nTNnzj1yGx9FxvJKK+b+6zZsFECNmi3x8+/Ghx92p169mgC816MvH37QnT/2rCG32zPcvp34JNJ4LBn5P7irVkB9SlYqw9rJK6zzBtT5gM/b/I/JPX/g1WFvUai4c6tUyaX33tnGpF7vbv779h6klncrGjdsR99+H5A9uyvZsmWjcpWK/DZ1LvXrtuHf6zfo0y9rjt/OatJ8P8nY5zWb0UjNWtX4v/cG0LZlV1r5NaNeg1p2a+vjePTjkuZC3EWqVmxMk/rtGDr4ayZNHUNut2esMZ3bv8tL5euRPbsr9Rs6N3975mk0Gpn821imTprN2cioJ9/4h5ChY+wDYl58sRxfjBrEJ5+Yh4tWqlSB0mVKsGpl5hhrDo/3fqYnIeEqPXsOZvbsiWzatJizZ6O4c+fO4zdWOERGOuf7gOpKKTfgFrAbc4e3PpAAbNVaX9Ja3wHmAncHqZmAJSm2tQKYrrWelc5r/am1jtJaJwEHgJLAC8BprfUZS8y8ZPENgDkAWuvVQHyyZT2VUgeBPUAxoJzW+l9gM+CnlHoBcNFaH07ZCKVUD6XUXqXUXpPpn/v93zxQdHSsTZXX09OdmNgLKWLirN9ojUYjefK4ceVKwgO3/fPP33Dy5Bkm/PTbY7XxUURHxdp8C08zr6h7uRuNRvLmzcOVK/FERadeNzbGvG6sZRuXLv3F8hVr8PauAkBExCla+75GzVqtWLBgBadPR9ozvQyJj/uL/B73LnF41r0ACRfjU8VVqPsyfh93YPy7X3Pn9r2D493YS+cvcmxPGMUrlrJ/ozMoOjrOuMO2nQAAIABJREFUZqiUp2cR4lK8vzHJYoxGI3nyuhGfYr89HnGKf6/foEKF54mOjiU6Oo59ew8CsGL5GipXrmjnTARATMwF669TYK683v3J/15MHB6e995PtzxuxMcnEBNzgd07Q7hyJYEbN26yaUMwlSpXcGj7MyomOg7PZHl6eBYmLs42z9iYODyT5ZnHkuft24nEx5v330MHwog8c44yZW0/k7du3WZt0GZatbYdQuJo9sxz7I9fcPpUJL/+MtMBmdxfdHQcRT1tzxWp9ttkMSnPnx6eRZg3/1fee7evtYBVo2Y1qlZ9mfCjO9i4aRFly5Vizdr5DsoobdFpnRNT5Jk8JqP9hKCgjTRo0JZGjdpx4sRpTp6MfOJtdzadZN+Hszywc661TgQiMVeZdwHbgcZAGeB+5dqbWmtTink7gVYqra+AZskHV5sw3+rxQb8rpPrqqJRqBDQDamutKwP7gRyWxVOB7tynaq61nqy19tJaexmNj3dXkL17D1K2bElKliyGi4sLnTu1ITBwg01MYOAGXu/WEYD27X3ZuvXBQ1RGjBhA3jxu9Os/4rHa96hC9h6gbNlS1ry6dG5LYOB6m5jAwPW8/nonADp08GWLJa/AwPV06dwWV1dXSpYsRtmypfgzZD+5cuUkd25zBSdXrpw0b9aQsDDzONdChcxjtZVSfPZpLyZPnu2oVNN15uBJCpd0p2DR5zC6ZKOmf10ObAixiSlesRRvjH6f8e9+zd9/XbPOz5XnGbK5mu9kmvtZN8pVf4HYE86tUiUXuu8QZcqUpESJori4uNC+ox9BQZtsYoKCNvFa1/YABLRrRbDlJ/C7P6MCFCvmQblypTh7LoqLFy8THR1L2XLmjkDDRnWIOJZ1LgjNyg6EHqZ0mRIUL+GJi4sLAR1as37NFpuY9Wu20PnVtgD4tW3BzmDzNR5bN+3gxYrPkzNnDoxGI7XrenM84pTDc8iI/aGHKVWmJMUt+21Ae1/WBm22iVkbtJkur7UDwD+gBTsseRYo8Kz1wvQSJYtSukxJzkae55lnclG4sPkHW6PRSDOfhpw4ftqBWaVmjzwBPh3Smzx5czN40GgHZpO+ffsOUqbsveNQx47+rF5te/5cHbSBrt06ANCuXWu2bTPfYyJv3jwsXTKd4cO+Zc+efdb4qVPmULZMTSq8WI9mTTtx8sQZWrV8xXFJpcHcT7h3Pu3UyT/NfkI3az+hNVu3PvheGnfPm/ny5aVHj9eZPn3eA9YQmUVG73MeDPQH3gYOA2MxV9T3AD9Y7pASD7wK3O8Ki2HAUOBnIKO32zgGlFZKldRaRwLJbw0QDHQFRimlWgF3B2DlBeK11tctFXLrb5Ba6z+UUsWAakClDLbhkZlMJnr3HkrgqjkYjUZmzFzA0aPHGTasH6H7DhG4egPTZ8xn+rQfCA/bzpUrCbz+xr3bEkZE7CKPmxuuri74+7fA168rf//9N58O6smxYyf4Y88aAH6ZNIPp0x337d9kMtGr9xBWr/4do8HAjJkLCA8/zvDh/dm37yCBgRuYNn0+M2aM52j4DuLjE+jazXx7qPDw4yxavIpDB7dwx2SiZ6/BJCUlUbhwIRYvMv8KYMxmZP785axfvxWAV7oE8MGH3QFYvjyIGTMXOCzX9CSZkpgzbCp9Zw3BYDSwY+FmYk5EEdCnC5GHT3Fg4146f/o62XPl4KOfzbcl+yv6MhPe+wb3skV5c3QPtNYopQj6ZRkxJzNP59xkMtG/30iWLp+B0WhgzuzFHDt6gs+G9GZ/6GHWBG1i9syFTJ46hv0HNxMfn8Db3XsBUKu2F336vU9i4h10UhL9+gznyl/mXwkG9hvJ1N/G4eLqQuSZ8/zfhwOdmeZDGTD8a0L2HyIh4RpNA7rx0Tuv0yHFRdCZlclk4rMBo5i3ZCpGo4F5c5YScewkAz/7hAP7j7B+zRZ+n72Yn379ht2ha0mIv8r7b5v32atXr/HrxBms3bwIrTWbNgSzcf02AIaO7E+7jr7kzJWT0DDzNr7/eqJT8/y0/+csXDoVg9HIvDlLiDh2kv991pMD+4+wbs1m5s5ezM+Tv+PP/euJj79Kj7f7AFC7rjf/+6wnd+6YSEoy0b/PcBLir1KoUAFmz/8FV1dXjEYDO4L3MGOacyut9sjT3aMwfQd8yPGIU2wONl9I+tuUOcyZtdipefbrO4wVK2dhNBqZNWshR4+eYMjQPoSGHiZo9UZmzljI1N/GcujwVuLjE3jzjU8AeP+DNyhdpgSDPu3JoE97AtDG/3UuXfrLafmk524/YdWq2RiNRmZa+wl92bfvMKtXb2DGjAVMm/YDYWHBXLmSwBtvfGxdPyJiJ27J+gl+ft04duwEY8aM4OWXzb9yjR79AydPnkmvCVlWkhPHhduTysjYZqVUU2AtkE9r/a9S6jgwSWs9Vin1GvAp5gp3kNZ6oGWdf7TWuZNtIxLzcJi/gGnAJa31wLtxlmp3f621nyX+J2Cv1nqGUsof+A64DPwJFNZad7WMI58HFAS2Ae2B6sDfwHLAE4jAPE59hNZ6q2Xbg4AqWusHfl3OnqPYU3qLe1t3777wtHvd48F3ZngaLLm8/8FBT4HLkRseHPSUKFbW19lNsDuTM39HFk/c9cRbDw56Cpj+I+dPgJs3z2Wq3vDxF1vatY9W/uhap+Sbocq51noT4JJsunyy578Dv6exTu4U0yWTTb6VMs7Scd6abP7HyeK3aK1fsAyHmQjstcT8BSS/31CfZM/vd8+gesC4+ywXQgghhBCZmDPvqGJPzv8zZxnznlLqABCGecjKr4+yEaVUPkvV/4blC4cQQgghhBCZRkbHnDuV1nocT6DSrbVOAMo/MFAIIYQQQmRqzvwrnvaUJTrnQgghhBBCJOfkP9ZrN1llWIsQQgghhBBPPamcCyGEEEKILOdpHdYilXMhhBBCCCEyCamcCyGEEEKILOdp/SNEUjkXQgghhBAik5DKuRBCCCGEyHLkjxAJIYQQQggh7Eoq50IIIYQQIsuR+5wLIYQQQggh7Eoq50IIIYQQIsuRu7UIIYQQQggh7Eoq50IIIYQQIsuRu7UIIYQQQggh7Eoq50IIIYQQIsuRu7UIIYQQQggh7Eoq50IIIYQQIst5Wu/WIp3zB1A8nW98Sm7Zczm7CQ6x+FKos5vgEElP6299/2HnT652dhMcovpLXZ3dBLv7r5xX1r6c3dlNcIgKB847uwniKSOdcyFEllWsrK+zm+AQ/5WOuRBCPAy5W4sQQgghhBDCrqRyLoQQQgghspyndcy5VM6FEEIIIYTIJKRyLoQQQgghspyn9dYH0jkXQgghhBBZjgxrEUIIIYQQQtiVVM6FEEIIIUSWI7dSFEIIIYQQQtiVVM6FEEIIIUSWk+TsBtiJVM6FEEIIIYTIJKRyLoQQQgghshyNjDkXQgghhBBC2JFUzoUQQgghRJaT9JT+FSKpnAshhBBCCJFJSOVcCCGEEEJkOUky5lwIIYQQQghhT1I5F0IIIYQQWY7crUUIIYQQQghhV9I5d4DmzRty6NAWwsKC6d//o1TLXV1dmT17ImFhwQQHr6BEiaIA5M+fj3Xr5nP58lHGjfvcZp2OHf0JCVlHaOhGvvzyM4fk8SBNm9Xnj9B17D2wkV59e6Ra7urqym8zfmDvgY1s2LyYYsU9bZZ7FnXnXOwBPu75js18g8HA1h0rmLdosl3bn1HNmjdg3/6NHDi0mT79Pki13NXVlekzx3Pg0GY2b11KcUue1atXYsfuQHbsDmTnntX4+ftY1zkcHszuP9ewY3cgW7evcFgu99OseQNCD2zi4OEt9E0nz5mzJnDw8Ba2bFt2L0+vyuzas5pde1aze08Q/m3u5fnzpG84ExnCnyFrHZbHgzRuWo8dIUHsDl3Lx73fTbXc1dWFX6eNZXfoWoI2zqdYcQ/rshcrlidw/Ty27V7Flp0ryJ7dFYBBQ3qx78hmTkXtdVgeT8qQ0WNp4PsKAd1Sv+dZTd3GtVi5Yz6Buxfx9sevp1pevVYVFqyfQWjUdpr7NbbOf75iOWYHTmbptrks3jybFm2bOrLZD61O45qs2DGPVbsXpplntVpVmL9+OvuigmmWIs9ZgZNZum0OizbPyvR5Zq/pTaHfZ1Jo/hye6fZqquU5W7XguVXLKDh9CgWnTyGnX2vrMrcPe1Bw1jQKzppGjiaNU62bmTRt1oA/Q9ez7+Amevd9P9VyV1dXfpv5I/sObmLDltTn0qJF3TkfdzDVufRplGTnh7Nkis65Uqq7Usoj2XSkUqqgHV4nSCmVz/JI3Uu2A4PBwI8/jqJt2zepUqUpnTu34YUXytnEdO/ehYSEq1Ss2IAJE6YyatSnANy8eYuRI8cwaNCXNvH58+fjq68+o1WrV6lWrRmFCxekceO6jkgnXQaDgW/HjKBz+3ep7d2KDh39eP75sjYx3d7oSELCNbyqNOOXidMZ8fkAm+Wjvx7Mpg3Bqbb9wUdvcjzilF3bn1EGg4ExY0fSod1beFdvQcdO/jz/gm2eb7zZmYSEa1Sp1ISJP01j5Bf/AyA8/DgN67WlXm0/2gd058cJozAajdb1fFu9Rr3afjSq39ahOaXFYDAwdtzntA/ojlc1Hzp1asMLKfJ8s3tnEhKuUvnlxkyc8BtfjBoEQHhYBPXrtqFOLV8CAt5k/PgvrXnOnb2EgIDujk4nXQaDga++H8prHXvQoKY/7Tr6Uv75MjYxr73ekYSEq9Su1pJff57FkBH9ATAajUyc/C0D+46gYW1/2vu9SWLiHQDWr91Kq6ZdHJ7PkxDQujmTxo5ydjMem8Fg4LOv+vHha30JaPAqrdo1p3T5kjYxsdFxDOn1BWuWbbCZf/PGTQZ/8jntG3blw1f7MPDz3rjlye3A1mecOc/+fPRaP9o1eI2W7ZqlyjMuOo6hvUalmeeQTz6nfcNufPRqXwZ83ivT5onBQJ6+vbjSfxCXunUnZ7OmZCtZIlXYzc1buPzWe1x+6z1uBAYBkL12LVzKl+PyW+/yV4+PeOa1LqhcuRydQYYYDAa+GzuCTu3foZZXSzp08kt1jnn9zU5cTbhK9cpNzefSLwbaLP/ym8FsTONcKrKOTNE5B7oDHg8KygilVLrj6LXWrbXWCUA+wCGdc2/vKpw6FcmZM+dITExk0aJV+CermAL4+/swZ85iAJYuDbJ2tK9fv8GuXSHcunXTJr5UqeKcOHGGy5evALB58w4CAlo5IJv0VfeqxJnTZzkbeZ7ExESWLllNKz/bKkxr32bM/30pACuWr6VBo9r3lvk1IzLyPMeOnrBZx8OjCM1bNGL2zIX2TyIDvLwqc/r0WSIteS5ZHIivX3ObGF+/ZsybuwSA5cvW0KhRHQBu3LiJyWQCIEf27OhMfH9WL6/KnD51L8/Fi1elztO3OXPnmPNclsE8d+78k/grCY5JIgOqVq/EmdPnOHc2isTERJYvCaJF6yY2MS1aN2HhPPOvGYEr1lGvYS0AGjWpS/iRCMKPRAAQH59AUpK51hK69yAXL1xyYCZPjleVl8mbx83ZzXhsL1WtwLkzUUSfi+FO4h3WLt9I4xYNbGJizsdx4ugp6/t219nT5zl3JgqASxcuc+VyPM8WyOewtj+Ml6pW4HyKPBu1qG8T8zTk6fLiC5iiYjDFxMKdO9zYuJns9TJWlMpWsgS3DxwEUxL65k3unDxF9lo17NziR1Pdco6xnksXr6a1bzObmFa+zZg3dxkAK5atpWGKc+nZM6nPpU8rjbLrw1keqXOulBqolOppeT5OKbXZ8rypUmqOUspHKbVbKRWqlFqklMptWT5MKRWilDqilJqszDoCXsBcpdQBpVROy8t8Yln/sFLqBcv6zyilplm2sV8p1dYyv7vldVYB65VS7kqpYMv2jiil6lvi7lbkvwbKWJZ/9+j/fQ/m4VGEqKgY63R0dCweHoXTjTGZTFy79jcFCjyb7jZPnTpL+fJlKFGiKEajEX9/H4oWfSLfbR6Zu3sRoqNjrdMx0XG4u9vm6e5RmOioOMCS59V/yF/gWXLlykmvPj349qsJqbY7+pvBjBj6baqTirO4exQhKip5nrF4pJHn3Zi772d+y/vp5VWZP0LWsvvPNfTuOcTaidVas3zlTLbtWEH3t15xUDbp8/AoQlSy9zM6Og4PjyIpYgpbY0wmE1eT7bde3lUI2buOP0LW0qvXYGuemY27+3PERMdZp2NjLqTeb90LE5Msz7+v/U3+/PkoXbYkGpi3ZArrty3h//4DPyFnJYXdC3Eh5qJ1+kLsRZ5zL/TQ23mpagVcXFw4Hxn9JJv3xDznXoi4mAvW6Yuxlyj8SHm+mKnzNBYqiOnivfcz6dIljIVS/8Ceo2EDCs6YSr4vRmB4zvz/kHjyFNlr1oTs2VF58+BarQrG5x7+/8gRzOfJFOfSVH2GezGpz6Xv800a51KRtTxq5TwYuPvV3AvIrZRyAeoBh4EhQDOtdTVgL9DXEvuT1tpba/0SkBPw01ovtsR01VpX0VrfsMRetqz/C9DfMm8wsFlr7Q00Br5TSj1jWVYbeFNr3QR4DVinta4CVAYOpGj/IOCU5fUGYEdKpf7mpVOUTDMSk1xCwlV69hzM7NkT2bRpMWfPRnHnzp3Hb+xjSCOFDOc5aHBPfvlpOv/+e91mmU/Lxly69BcHD4Q90bY+jgzlmda3bUvM3r0HqendkkYNAujX/0PrGGWfpp1oULcNHdq9zXvvv06dut5PvO0P43H3270hB/D2akHD+m3p1/8ja56ZTZo5kJE8IZvRSM1a1fi/9wbQtmVXWvk1o16DWnZrq3hID3lcTUvB5wowesIwhvUe9dDrOkpGjkkPUvC5Anw5YRjDen+ZafNMJ1GbyZs7d3Ox06tc7v4ut/fuI99g81C72yF7ubVnDwUn/cSzI4aSeCQcbcocBZ+UMtQfSPdc2otfJqY+lz7NntYx5496K8V9QHWllBtwCwjF3EmvD6wEKgA7LTuZK7Dbsl5jpdRAIBeQHwgDVqXzGkuTvVZ7y3MfoI1S6m5nPQdQ3PJ8g9b6iuV5CDDN8oVhudY6Zef8vpRSPYAeANmyPYvR+Ohj8KKjY22q2p6e7sTGXkwzJjo6DqPRSJ48blx5wE//QUEbCQraCMA777yGyckHmpiYODw93a3THp5FiIuzzTMmOg7PokWIibHkmTc38VcSqO5VmTZtWzLii4HkzZuHpKQkbt68hbtHYVq1bkpzn4Zkz5EdN7fcTJryPR+81z/lyztMTHQcRYsmz9Od2JR5xphjrHmm8X4ejzjFv/9ep0KF59m//7D1/+rypb8IXLnefFHlzhD7J5SO6OhYiiZ7Pz09ixAbeyFFTBxFPd2Jsey3edPIMyLiFNf/vU6Fis+zP/SwQ9r+MGJiLuDhee8XAXePwsTFpn4/PTzdiY25gNFoxC2PG/HxCcTEXGD3zhBrzps2BFOpcgV2BO9xaA4ibRdiLlLY4znrdGH357gUdznD6z+TOxcT54xhwjeTORSaeQoEKV2IuUSRZJXV59wLcfEh8/xpzvf89M1kDmfiPE0XL2F87t77aShUCNPlv2xi9LVr1ufXV63G7cN7Nyb4Z9Zc/pk1F4B8w4dgOh9l5xY/GvN5MsW5NOUxyRKT8lzq5V2ZtgEtGZnsXHrr1m2m/Drb0WmIx/RIlXOtdSIQCbwF7AK2Y65klwHOYO4oV7E8Kmit31FK5QB+BjpqrV8GpmDuXKfnluVfE/e+RCigQ7JtF9daH7Us+zdZ+4KBBkA0MFsp9cZD5jdZa+2ltfZ6nI45mCulZcuWomTJYri4uNCpkz+BgbYX5QQGbqBbt44AtG/fmq1bdz1wu4UKFQAgX7689OjxOtOnz3usdj6u0H2HKV2mJMVLFMXFxYX2HXxZu3qTTcyaoE288pr5e1bbgJZs32buxPi2eI0qLzWmykuNmfTzDMaNmcTUyXP4YsQYXnqhPlVeasy73XuzPXiPUzvmAPv2HaJ0mZKUsOTZoaMfQas32sQErd7Eq107ABDQrhXbtpm/m94dhgRQrJgH5cqX5uy5KHLlyknu3OYfgHLlykmTpvU4Gn7cgVmltm/fIcqUvZdnx47+qfMM2kjXbuY826Wbpyflypfm3NnMeSI8EHqY0mVKULyEJy4uLgR0aM36NVtsYtav2ULnV80X6fq1bcFOS+d766YdvFjxeXLmzIHRaKR2Xe9Mc+GygLADRylRuhiexd3J5pKNlgHN2Lp+e4bWzeaSjR+mf8OqRWvYsGqznVv6eMIOHKV46aI2eW5bvyND62Zzyca46V9b8tzy4BWcKPHYMYzFPDG6F4Fs2cjZrAm3dtqeKw0F8lufZ69Xhztnz1kWGFB58gCQrUxpspUpza0Q5xU/7id03yHKlClx71za0Zc1Qbbn0rVBm3i1azsA2rZrSbDlXNra51UqV2xE5YqN+OXnGYz9/penvmMulfPUgjEPN3kb81CWsZir3HuAiUqpslrrk0qpXEBR4O5Xv8uWMegdgcWWeX8DGbkCaR3mseifaK21Uqqq1np/yiClVAkgWms9xTLspRowK1lIRl/vsZlMJnr3HsqqVbMxGo3MnLmAo0ePM2xYX/btO8zq1RuYMWMB06b9QFhYMFeuJPDGGx9b14+I2Imbmxuuri74+7fAz68bx46dYMyYEbz8cgUARo/+gZMnzzginXSZTCYG9h/J4uXTMBqMzJ29mGPHTvLp4F7s33+YtUGbmTNrEZOmfM/eAxuJj0/g3bf6OLXNj8JkMjGg3wiWrZiJ0Whg9qxFHDt6gsFDehMaepg1QZuYNXMBk6eO5cChzcTHX+WtN3sCULuOF336fkDinTskJSXRt/cwrvwVT8mSxZg7fxJgHiqxaOFKp19pbzKZ6Nd3OMtXzrLmefToCYYM7UNo6GGCVm9k5owFTP1tHAcPbyE+/ird3/gEgNp1vOnX716efXoP5a+/4gGYPuNH6jeoRYECzxJxYhdfjvqBWU682NdkMvHZgFHMWzIVo9HAvDlLiTh2koGffcKB/UdYv2YLv89ezE+/fsPu0LUkxF/l/bf7AXD16jV+nTiDtZsXobVm04ZgNq7fBsDQkf1p19GXnLlyEhpm3sb3X090Wp4PY8DwrwnZf4iEhGs0DejGR++8Tgf/Fs5u1kMzmUyM/mwMv8z7AaPRwPJ5gZyKOMNHA98j/MBRtq7fQcUqL/LDtK/Jk8+Nhs3r8eGAd2nfsCst2jSlWq0q5H02D226mG/HN7TXKCLCMt9FdiaTia8+G8sv88ZhMBqT5fkuYQeOsc2S57hpX1nz/GjAO7Rv2C3NPIf1+jJT5okpiWtjx5N/7LdgMHBj9RrunIkk9ztvkXgsgls7d/FMx/bmi0RNJpKuXSPhy6/N62YzUmDijwDo69dJ+PxLyKTDWkwmEwP7jWTJ8ukYjUbmzjafYz4d0osDoUdYE7SJ2TMXMmnqGPYd3ER8fALvdO/t7GY7zdP6R4jUo44vU0o1BdYC+bTW/yqljgOTtNZjlVJNgG+A7JbwIVrrlUqpUcArmKvu54GzWusRSqkOwGjgBuax40cBL631ZaWUF/C91rqR5WLRH4A6mKvokVprP6VUd0v8x5a2vQkMABKBf4A3tNZnlFKRybb7O1AJWHO/cec5chTPpAPwnqxcLtkfHPQUuJOUOS9MfNKSMuu40Scst+v9fnx7epw/udrZTXCY6i91dXYT7C7N61KeQmvL/jfOKxUOnHd2Exwm/p+TmWrnXV34Vbue7HwvzHNKvo/cOf+vkM7500U6508X6Zw/faRz/vSQzvnTJ7N1zlcVsW/n3D/OOZ3zzHKfcyGEEEIIIf7zHmfMuRBCCCGEEE6R9JT+CiWVcyGEEEIIITIJqZwLIYQQQogs52m9ukoq50IIIYQQQmQSUjkXQgghhBBZTua8W/3jk8q5EEIIIYQQmYRUzoUQQgghRJaTpORuLUIIIYQQQgg7ksq5EEIIIYTIcuRuLUIIIYQQQgi7ksq5EEIIIYTIcuRuLUIIIYQQQgi7ksq5EEIIIYTIcpKezpu1SOVcCCGEEEKIzEIq50IIIYQQIstJ4uksnUvlXAghhBBCiEeglGqplIpQSp1USg26T1xHpZRWSnk9aJvSORdCCCGEEFmOtvPjQZRSRmAi0AqoALyqlKqQRpwb0BP4IyN5SedcCCGEEEJkOUnKvo8MqAGc1Fqf1lrfBuYDbdOI+wL4FriZkY3KmPMHGFq4vrOb4BAH+MfZTXCINZcOObsJDnHzzm1nN8Ehcrq4OrsJ4gnbd2Sus5vgGKZEZ7fA7mpUftvZTXCIl/KWcHYThJ0opXoAPZLNmqy1npxs2hM4n2w6CqiZYhtVgWJa60ClVP+MvK50zoUQIpOr/lJXZzfBIf4zHXMhxBNh7z9CZOmIT75PSFr1deuIGKWUARgHdH+Y15VhLUIIIYQQQjy8KKBYsumiQEyyaTfgJWCrUioSqAWsfNBFoVI5F0IIIYQQWU5GLtq0sxCgnFKqFBANvAK8dneh1voqUPDutFJqK9Bfa733fhuVyrkQQgghhBAPSWt9B/gYWAccBRZqrcOUUp8rpdo86nalci6EEEIIIbKcDN5Rxa601kFAUIp5w9KJbZSRbUrlXAghhBBCiExCKudCCCGEECLLsffdWpxFKudCCCGEEEJkElI5F0IIIYQQWY5UzoUQQgghhBB2JZVzIYQQQgiR5ehMcLcWe5DKuRBCCCGEEJmEVM6FEEIIIUSWI2POhRBCCCGEEHYllXMhhBBCCJHlSOVcCCGEEEIIYVdSORdCCCGEEFmOdnYD7EQq50IIIYQQQmQSUjkXQgghhBBZTpLc51w8CaUbVuKDzd/x4bYx1P7QP9Xyal2b8t66r3k3aDRvLB5GwXKeAHhULs27QaPNjzWjeb6Fl6Ob/lCqNKzKj5t/ZsK2SQR82CHVcr932zBu40/Ha9jEAAAgAElEQVR8v/ZHhv3+OQU9CwFQskIpvlz2DWM3TOD7tT9Sx6+eo5v+QM2aNyD0wCYOHt5C334fpFru6urKzFkTOHh4C1u2LaN4cfN72LhJPbbvXMkff65h+86VNGxY27pOhw6+7PljDSF71/HFqEEOy6WFTyPCjvw/e/cdV1X9BnD8c+4FnDhAZDkwtXJj7r01B4ppWmmONE1/Zu5ym+bKlVaWpuZeuQcqIi7MBYILByKo7K2VA7ic3x/QlSsOLO+9YM/79eIl93yfc3gez+Xec5/zPYdjXA30Yczo/z21lvXrfuJqoA+/++ymdOkS+rEvxwzhaqAPly8do3WrJi/c5uBBfbga6ENqcji2tkX1y0eO+Azfs574nvUkwP8Qjx7cpmjRIkaqOKvmLRpx0nc/Z/w9GTr80yzjVlaW/PLrAs74e7L/0GZKZuzPkqWcuR11nsPHd3D4+A7mLPhav86mrcs47LOT46f2MGfB12g0OeultkGzuuzy2ciek7/xyZCPs4zXqOvKJs+VnAs7TqsOzfTL36pUnjV7lrLt6Dq2eK+hTacWpkz7lZowYz6N23+Ae8+sv8O5jc9pPzr0GETbDwewbO2WLOMRUTH0GzaBzn0+p8/QcUTFxOnH5v+0EvfeQ3DvPYR9h46bMu2XVr9ZHbb7bGDnyU30HdIzy/g7daux3nMFZ8OO0rJDU/1yxxL2rDuwnI1eK9lydC1de7mbMOuXV7tpLdYdW8kGn9X0+N8HWcar1anC8v0/c/iWJ03bNzYYK+5UnHnrZ7PmyArWHF6BQwl7U6VtFmlG/jKXHN85VxSlCPCRqqqLzZ3Lv6VoFN6d1of1PWZyLyqBT3ZNI8jrHHFB4fqYSzt/59y6QwCUb/kOLSf0YGPvb4m5FsZytwmoujQKFi9C/30zuO51DlWX865V1mg09Js2kGk9JpMQFc/MXXPx9TpDWNAdfUzI5RC+7DCC5IfJtO75Lh+P7cOCIXN49OAR3w//jqjQSIoWt2H23nkEHPPn/r2/zFjRYxqNhvkLptKxw8eEh0dx7PhOPPZ6cfXqDX1M7z7dSEq6S7UqzejatQPTvvmK3r0+Jz4+gfe79icqMoaKFd9kx65VvFmuHjY2RfhmxlgaNehIXFwCS5bOpWnT+hw58rvRa1m0cDrvtvuQsLBITp30YPceT65cCdLHfNL3QxIT7/J2xYZ069aRmTPG81GPQVSoUJ5u3TpR1bU5Tk72HNi3kQqVGgE8c5u/nzzLXg8vDh00PHiYN/9n5s3/GYAO7VvxxdBPSUxMMmrtmf8PZs2bxPvufYkIj8bz8Bb2e3hz/VqwPqZHr/dJSrpH7eqtce/Sjklfj+LTvsMBCA25TbNGWd/o+/X5gj//SH/O/rpmER07v8uOrR4mqelFNBoN42aOZEC3L4iOjGHD/hUc8TzOzeuh+pjI8CgmfDGNPoN7GKz78MFDxn8+ldshYdjZF2Oj56/8fvg0f9z708RV/Hvu7VrxUZeOjJs219yp/Cs6nY5vFizhl/lTcbCzpfuAkTRrWJuyLqX0MXMXr6Bjm2Z0atuC037n+W7pamZNGMHRk2cJDApmy/KFJKek0GfoOBrVrUHBAvnNWNHTaTQavpo5kkHdhhEdGcO6/cs46unzxPM2mslfTKfX4A8N1o2NjqeP22ekJKeQL38+thxdw9EDPsRGx5HTaDQaRkwfyvAPxxAbGcsvHos54XmS0KBb+pjo8BhmDP+WDz57P8v6ExZ+yepF6/E97ke+/HlJS3tdZ2W/3nJWO+fpigCDzZ3Eq+DkWpaE0GiS7sSSlqIjcPcp3mxVwyAm+c8H+u8t8+fRf5/6MFl/IK7NY4mag3/fyrmWJyo0ipg70aSmpHJi93FqtqptEHP55EWSHyYDcN3/GjaOtgBEhkQQFRoJQGJMAnfj7lLIppBpC3iOmjWrcTP4FqGhd0hJSWHLlt2079DKIKZ9+1asW7sVgO3b99G0aX0ALpwPJCoyBoDAwOvkyZMHKysrXMqU4kZQCHFxCQAcPnyCTu7vGr2W2rWqExwcSkjIbVJSUti8eScd3doYxHR0a82aNb8BsHXrXpo3a5ixvA2bN+8kOTmZ0NA7BAeHUrtW9eduMyDgMrduhT03p+7dO7Fx0w4jVPt079SoSujNW9wKDSMlJYUd2/bStr1hN7htu+ZsWr8dgN07DtAo0xmPZ/n7wNzCwgJLS0ty0i9s5eoVuR0SRvjtCFJTUtm/w4tmbQy7bxF3ogi6EkxamuGH/1s373A7JH0fxkbHkRCXSFFb053leJVqulahcCFrc6fxr128EkQpZ0dKOjlgaWlJ2xaN8PY5bRATHHqHOjWqAVD7naoczhgPDr1DrWqVsbDQkj9fXt4q64LP6XMmryE7KlevwJ1Mz9sDOw7RtE0jg5hI/fPW8PctNSWVlOQUAKzyWKIoOXcuRIXqbxMeGk7k7UhSU1I5tPMwDdvUN4iJCosm+MpN1CfqdClfGq2FFt/jfgA8uP+QRw8fmSx3c3hdO+e54eB8FlBWUZQARVHmKIoyWlGUs4qiXFAU5WsARVFcFEW5qijKMkVRLimKsk5RlJaKopxQFCVIUZTaGXFTFEVZoyiKd8byrOewjcjawYY/IuP1j+9FJmDtUDRLXI1erRh8bD4txn7Igcmr9MudXMsy4OBsBhyYxf7xK3Jk1xzAxsGW+MjHHYmEyHhsHWyfGd+ieyv8j/hlWV6uWnksrCyIvhVllDz/CScnB8LCI/WPw8OjcHJyeCLGXh+j0+m4e+8Pg2kcAO7ubblw/jLJycncDA7lzbfKUqqUM1qtFje3VjiXcDJ+Lc4O3AmL0D8OC4/MWkumGJ1Ox92797C1LYqT01PWdXbI1jafJV++vLRp3ZRt203XYXZ0sic8/PHzKyI8GkdHw9PADo72hGfan/fu/YGNTfr+LFW6BN7Ht7Nz7xrq1jP8oL152zKuBP/On3/+xa4dB4xcSfbZO9oRHRGjfxwdGUNxR7uX3k7l6hWxtLTkTmj4i4OF0cTExeNQvJj+sb1dMWJi4w1i3ipXhoNH08/EeR07yV/3H5B09x5vlS3D8dN+PHj4iMSke5z1v0hUTKxJ88+u4k953tq9xPPW3qk4m7xXsc9vOyt/XJcju+YAdg7FiIl4vA9iI2Mp5lDsOWs8VvKNEvx57y+++WUKyw/8zOAJA3LclDqRPblhr30FBKuq6gocBMoDtQFXoIaiKH+3fMoBC4GqwNvAR0BDYBQwLtP2qgLtgXrAJEVRjH8U9BzqUzpqfqsPsrjxCLxnbaTh549PmUcEBLO01Zes6DiR+oM7os1jacpU/5Wn1QnQqHMT3qhSjl1LthssL1K8KJ8vGM7iUYueua45PK3j8mR+L4qpUKE8U7/5kqGfjwcgKekew76YyKo1P+DptZlbt8LRpaa+4syz+ue1PHvd7GzzWTp0aM3vJ31NNqUF/t3+jI6KoXqlZjRv1JmJ42fx87J5FLQuoI/p9l5/Kr/ZkDx5rGjUpO6rT/6f+hf76G/Fitsy4/tJTBr2TY76/fwvetr//5PP2VGD++IbcImu/b7AN+Ay9na2aLVaGtSuTqO6Nek5eAyjp86hWqW30Wq1pkr95Tyt2/0Sz73oiBi6N+9Np3rdcevWFptiWRtjOcLTmvrZrFNroaVq7cr8OG0JA9oNxrGUI227tXnxirmYauQvc8kNB+eZtc748gfOkX4QXj5jLERV1YuqqqYBl4FDavqr1kXAJdM2dqqq+kBV1TjgMOkH+gYURRmgKIqvoii+Z/+88eTwP/ZHVALWjo87yIUcbfgz+tkHIpd3neTN1lkv/Iy/EUHyg0cUf7PEU9Yyv4SoeGwdH3/St3G0JSE6IUtclQbVeG/I+8zuP53U5McHo/kK5mPsrxPZMHctQf7XTZJzdoWHR1LC2VH/2NnZgcjI6CdiovQxWq2WwoWsSUhI389Ozg6s37iEAf1HEhJyW7/OPo9DNGvSmRbNuhAUdJMbN0KNX0tYJCUzdehLODtmrSVTjFarpXDhQiQkJBIe/pR1I6Kztc1n6d6to0mntABEhEfh7Py4s+/kbE9UVIxBTGREFM6Z9mehQtYkJiaRnJyi/yBxIeAyoSG3KVuujMG6jx4ls9/Dm7btcs6Fk9ERMdg7Fdc/tncsTmxU9ruIBQrm58e18/h+9lIunLtsjBTFS7C3K2ZwgWd0bBx2xWwMYooXs2Xh9HFsWb6QLz5Nv5DSumD6B8mBvbqxdcVCls2fhopKaROctfsnYv7l8/ZvsdFxBF8L4Z261V5leq9MbGQcxZ0enxGwc7QjLjr+OWs8FhMZS9ClG0TejkSnS8PnwAnerFL+xSuKHCe3HZwrwExVVV0zvsqpqro8YyzzxKq0TI/TMLzw9ckPQ1k+HKmqulRV1ZqqqtasVbDcq8qdiPM3sSnjQOGSdmgstVR0q8v1g4bTOYq6PD6lXr65K4mh6afcC5e0Q9Gm765CzsWwfcORpLCcefrxxvkgHMs4UrxkcSwsLWjg1gjfg2cMYlwqlWHAzEHM7jede/F39cstLC0YvXQsR7ce5pSHcS+I/Cf8/C5QtpwLpUuXwNLSkq5d3fDY62UQ4+HhRY+e6Xeo6dy5LUePngSgcGFrtm5dwZRJ33LqlOF+t7NL/9BWpEghPh3Qk1UrNxm9lrO+AZQrVwYXl5JYWlrSrVsndu/xNIjZvceTjz9Ov+ioS5f2HD5yQr+8W7dO6XPmXUpSrlwZzpz1z9Y2n6ZQIWsaN6rLrl2mnf7hf+4iZcq6UCpjf7q/1579Ht4GMfs9vOn+UWcA3Nzb4HPsFAC2tkX1p4xLu5TgjbIu3Aq9Q4EC+bG3T39z1Wq1tGzdhKDrN01Y1fNdDrhC6TdK4lzKEQtLC951b8kRz+zdpcPC0oLvfp3N7t/2cXC394tXEEZX+e3y3A6LICwiipSUFPYdOk6zBnUMYhKT7umvH/hl3RY6t2sJpE/TSrp7D4BrwSFcDw6lfq3qpi0gmy4HXKXUGyVwynjetnFvwRFPn2ytW9zRjjx5rQCwLmyNa60qhN64/YK1zONqwFVKlHHGsaQDFpYWtOjUDB/P7L0XXg24hnURa4rYFAbgnQbVCb1+6wVr5W5pinG/zCXH360F+AP4+6qdA8A0RVHWqar6p6IozkDKS26vk6IoM4ECQFPSp82YhKpL48CklXy4+ks0Wg3nNx8lLiicxiO6EHkhhCCvc9Ts3ZoyDSuTlqLjwb2/2DUi/S4WJWu+Rf3BbqSl6FDVNPZP+JUHiTnzDglpujSWT1rK+NVT0Gg1HN58iLCgO3Qf8RHBF27g63WGj8f1JW/+fIxcPAaAuIg4ZvefTr0ODahQuxLWRaxp1rU5AD+OWkRoYIg5S9LT6XSMHDGZHbtWo9VqWLP6N65cCWLCxOGcO3cRj71erFq5iWXLF3D+4mESE+/Sp9fnAAz8rDdvlC3Nl2M/58ux6cs6ufUiNjaeb+dMokqVCgDMmrmIGzeMX69Op+OLYRPw2LserUbDylWbCAy8zpTJo/D1O8+ePQdZ8etGVq1cxNVAHxITk/ioZ/q12YGB19myZTcXzx8mVadj6Bfj9W/+T9smwJD/fcKokYNxcLDD38+Lffu9GfjZaADcO7XloNcx7t9/8PRkjfh/MHbUVDZvW4ZGq2XD2q1cu3qDL8cNJcD/Egf2ebNuzRYWL53DGX9PEhPvMuCT9Du11GtQiy/HDSU1VUdamo5RwyeTlHgXOztb1mz8CSsrK7RaDT7HTrFyxUaT1vU8Op2OGePm8dOG79BqNezYsIfgayEMHvMpgQFXOOLpQyXXCny3YhaFiljTpFVDBo3uz3tNetCmYwveqetK4aKF6Ni9HQATv/iGa5eDXvBTc57Rk2dx1v8CSUn3aOHek8H9PqaLW+6bAmBhoWXcsIEMHDUFXVoandu1pFyZUvywfB2V3ipHs4Z1OBtwke+WrEZRFGpUq8SE4em3j0xN1dFryFgAChbIx6wJI7CwyJnTWnQ6HbPHLWDxhvlotFp2btjDzWshDBrTn8CAqxz19KGi69vMXzGTQkWsadyqAZ+N7k/XJj0pU96FEVOG/D0nj9U/beDG1ZzzgTkznS6NBRO+Z9762Wg0GvZu2kfo9Vv0G9WHq+evceLgSd6u9hbTl3+NdeGC1G9Vj09G9qZX836kpaXx49QlfLdpLihw/WIQu9fvNXdJ4h9QcsN8QUVR1pM+V3wfEAb0zxj6E+gJ6IA9qqpWzohfmfF4i6IoLn+PKYoyBXACygKlgG9VVf3leT97eukeOf8/6BUIIGce6L9q+2IvmDsFk3iYmmzuFEyiaL6C5k7BJBzz2bw46DXgd2mduVMwHd3L9pVyn9rVPjF3CiZRUJvX3CmYzPHwQznqVjezSvc06jHaV7fWmqXe3NA5R1XVj55YtPApYZUzxffJ9H1o5jHguqqqA15lfkIIIYQQQrwKueLgXAghhBBCiMxe16kN/6mDc1VVp5g7ByGEEEIIIZ7lP3VwLoQQQgghXg9pr2nvPLfdSlEIIYQQQojXlnTOhRBCCCFErpNm7gSMRDrnQgghhBBC5BDSORdCCCGEELnO6znjXDrnQgghhBBC5BjSORdCCCGEELmOzDkXQgghhBBCGJV0zoUQQgghRK6Tppg7A+OQg3MhhBBCCJHryB8hEkIIIYQQQhiVdM6FEEIIIUSu83r2zaVzLoQQQgghRI4hnXMhhBBCCJHryK0UhRBCCCGEEEYlnXMhhBBCCJHryN1ahBBCCCGEEEYlnfMX0PKa3uH+CRb/kTo1yn+jzv9Glf8diuzR14/W0twZGN2ZS2uoX7WPudMwunya139f5lSvZ99cDs6FEELkFLoUc2dgGv+BA3MhxD8nB+dCCCGEECLXkbu1CCGEEEIIIYxKOudCCCGEECLXkbu1CCGEEEIIIYxKOudCCCGEECLXeT375tI5F0IIIYQQIseQzrkQQgghhMh15G4tQgghhBBCCKOSzrkQQgghhMh11Nd01rl0zoUQQgghhMghpHMuhBBCCCFyHZlzLoQQQgghhDAq6ZwLIYQQQohc53X9C6FycC6EEEIIIXKd1/PQXKa1CCGEEEIIkWNI51wIIYQQQuQ6r+u0FumcCyGEEEIIkUNI51wIIYQQQuQ6citF8UqUaVKVT73nMPDoPOoOcssy7tqjOZ8cmElfj+n02DIR2/JOBuOFnGwZEbiM2gPamSrlf6Rak+rM8/6RBUd/ouOg97KMt+vfkTle3zN7/3eMXz+VYs52ABRztmP6nnnM9FjAnIOLaNmjjalTf6GWrRrj5+9FwAVvho/8LMu4lZUVv65aRMAFb7yPbKNUKWcAatSois/JPfic3MOJU3vp4NYagDx5rDh8dDsnTu3l9Nn9jBs/zKT1ZNa6dVMuXTrGlUAfRo/+X5ZxKysr1q37iSuBPpzw2U3p0iX0Y2PGDOFKoA+XLh2jVasmALz5Zll8z3rqv+LjrjL08/4ATJw4gtAQX/3Yu+82N02RT2jeohEnffdzxt+TocM/zTJuZWXJL78u4Iy/J/sPbaZkxv4sWcqZ21HnOXx8B4eP72DOgq8ByJcvL+s3L+H3s/s4fmoPE6eMNGk92VG/WR12+mxg98nNfDLk4yzj79R1ZaPnr/iFHaNlh2b65W9VKs/qPUvZdnQtv3mvpk2nFqZM+6X5nPajQ49BtP1wAMvWbskyHhEVQ79hE+jc53P6DB1HVEycfmz+Tytx7z0E995D2HfouCnTfqUmzJhP4/Yf4N4z62tVblOvaW22HF/LthPr6T2kR5bx6nWqsebAMk7e9qZ5+yZZxgsUzM9ev62Mnm6+19jsqNm0BsuPLOPX4yvoPrhblvEqdSrzo8cP7AvZS6N2DQ3G+o/rx1KvJSzzXsrgrweZKmXxiuX4zrmiKONUVZ1h7jxeBUWj0Hpabzb2mMUfUQn02TWVIC8/4oMi9DGBO08SsM4bgHIt36HFhJ5s7v2tfrzFpB7cPHLe5Lm/DEWjoe+0gczoMZn4qHim75qDn9cZwoPC9DGhl28yvsNIkh8m07Lnu3w0tjeLhswlMSaRye99SWpyKnny52WO5yL8Dp4hMSbRjBU9ptFomDf/azq59SI8PIojx3fgsdeLa1dv6GN69e5GUtI9XKs2p0vXDnw97Uv69h5KYOB1mjTshE6nw97Bjt9P7WWfxyEePUqmQ7se/PXXfSwsLPD02sxBzyOcPRtg8toWLZxO23YfEhYWyamTHuzZ48mVK0H6mE/6fkhS4l0qVGxIt24dmTFjPD16DKJChfJ079aJaq7NcXKyZ/++jVSs1Ijr14OpWau1fvu3Qv3YsXOffnsLF/3CggVLTFpnZhqNhlnzJvG+e18iwqPxPLyF/R7eXL8WrI/p0et9kpLuUbt6a9y7tGPS16P4tO9wAEJDbtOskXuW7f74/QpOHD+NpaUl23atpEXLxhzyOmayup5Ho9EwbuYoBnb7gujIGNbvX84Rz+PcvB6qj4kKj2LiF9/Qe/BHBus+fPCQCZ9P5XZIGHb2xdjguYLfD5/mj3t/mriKF9PpdHyzYAm/zJ+Kg50t3QeMpFnD2pR1KaWPmbt4BR3bNKNT2xac9jvPd0tXM2vCCI6ePEtgUDBbli8kOSWFPkPH0ahuDQoWyG/Giv4Z93at+KhLR8ZNm2vuVP4VjUbDmBnDGfLBCKIjY1nlsZRjB3wICbqlj4kKj+brYTPo+dkHT93GZ2P6c+6UaV9XX5ZGo2HIN//jq4/GERcZx/d7FnHy4CluB93Wx8SExzJ3xDy6DuxisG7FGhWoVLMin7VOPyifv20eVetW5cKpCyatwZRUmXNuNuPMncCr4uhalsTQaO7eiSUtRUfg7lOUb1XDICb5zwf67y3z5zF44pVvXYOk27HEXQ83Wc7/RDnX8kSFRhJzJxpdSiond/tQs1Udg5jAk5dIfpgMwA3/a9g42gKgS0klNTkVAEsrSxSNYtrkX6BmzWrcvHmL0NA7pKSksHXLHtp3aGUQ075DSzas2wrAju37aNq0PgAPHjxEp9MBkDdPHtRMryl//XUfAEtLCywsLVBV07/g1K5VneDgUEJCbpOSksKmzTtxczM8c+Hm1po1a34DYOvWvTRv1jBjeRs2bd5JcnIyoaF3CA4OpXat6gbrNm/ekJs3b3H7ds55/r5ToyqhN29xKzSMlJQUdmzbS9v2ht3gtu2as2n9dgB27zhAoyb1nrvNBw8ecuL4aQBSUlK4cD4QR2d74xTwD1SuXpE7IWGE344gNSWV/Tu8aNqmkUFMxJ0ogq4Ek5ZmeNL41s073A5J/5AdGx1HQlwiRW2LmCz3l3HxShClnB0p6eSApaUlbVs0wtvntEFMcOgd6tSoBkDtd6pyOGM8OPQOtapVxsJCS/58eXmrrAs+p8+ZvIZXoaZrFQoXsjZ3Gv9apeoVuBMaTvjtSFJTUjm48xBN2hh2jSPDorhx5SZqWtbXz7ervImNXVFOHz1rqpT/kbdc3yIiNJKo21GkpqRydNdR6rc2fM2JDosm5GpIlvcJVQWrPFZYWFlgaWWJhaWWxLic0dgSLydHHZwrirJDURQ/RVEuK4oyQFGUWUA+RVECFEVZlxHTU1GUMxnLliiKos1Y/qeiKLMz1vdSFKW2oihHFEW5qShKx4yYPoqi7FQUZb+iKNcURZlsyvqsHYryR2SC/vEfkQlYOxTNEvdOr5YMPDaPZmM/wGvyagAs8+Wh7qAO+Hy3zWT5/lNFHWyIj3x8ejg+Mp6iDjbPjG/avSXnjzx+47NxLMbs/d/xw6ll7Pp5W47pmgM4OjkQFhapfxwRHomTo/0TMfb6GJ1Ox717f2Bjm76fa9asxumz+zl5Zh/Dhk7QH6xrNBp8Tu4hOPQsh71P4Otr+rMjTs4OhIU9PosTHh6Js5NDlpg7GTE6nY67d+9ha1sUZ6es6zo5G67bvVsnNm3aYbBs8KC+nPM7yC9L51GkSOFXXdILOTrZEx4epX8cER6N4xP708HRnvDwJ/anTfr+LFW6BN7Ht7Nz7xrq1jP8oA1QqLA1rds24/jRk0as4uUUd7QjKiJa/zgmMhZ7R7uX3k7l6hWwtLTkTmjO+bCVWUxcPA7Fi+kf29sVIyY23iDmrXJlOHj0dwC8jp3kr/sPSLp7j7fKluH4aT8ePHxEYtI9zvpfJCom1qT5C0N2DsWIjojRP46OjMUum89bRVEYNvl/LJr2k7HSe2WKOdgSG/H4uRYbGYetg2221r1y7goBJ8+z0Xc9G/3W43vUjzs37hgr1Rwhzchf5pKjDs6BT1RVrQHUBIYCc4AHqqq6qqraQ1GUCkB3oIGqqq6ADvh74lkB4EjG+n8A3wCtgM7A1Ew/o3bGOq7A+4qi1HwyiYwPBr6Kovie+TPoyeF/4Sld4Kc0SM+t9mJJ45EcmbWR+p+nnzJvOOI9zi7bT8r9R68wH+NQslknQMPOTXijSjl2L9muX5YQGceX7w5jeOPPaNylGYWLmf6g7VmUp5X2RPfi6fWnx/j6nqdOrXdp2tidkaMGkSePFQBpaWk0rNeBCm/Wp0aNqlSo+OYrz/1FlKcUl6W2p8a8eF1LS0s6dGjNlq179MuWLFnNW2/Xp0bN1kRGxTDn20n/Jv1/5J/XrBIdFUP1Ss1o3qgzE8fP4udl8yhoXUAfo9VqWbp8Pst+XsOt0LAs2zCX7DyHX6RYcVumfz+JScOmm+UsT3Y8La8n9+WowX3xDbhE135f4BtwGXs7W7RaLQ1qV6dR3Zr0HDyG0VPnUK3S22i1WlOlLp4iO7+rz9K1T2dOeJ8yOLjPsf5FnU4ujpQqV4qPavfkw1o9cK3vSpU6lV91hsIEctqc86GKonTO+L4kUP6J8RZADeBsxi9qPuDv37ZkYH/G9xeBR6qqpiiKchFwybSNg6qqxgMoirINaAj4ZmIRTIQAACAASURBVP4hqqouBZYCzCrd85W98/wRlYC14+MOsrWjDX9EP7srHLjrFK2/6QuAk2s53m5bm2ZjPyBPofyoqkrqoxTOrTr4qtJ7ZRKi4rF1fNyxsnW0JTE6IUtc5QZVcR/SlandJuinsmSWGJNI2PU7vFW7Imc8ckbnMSI8ihIlHPWPnZwdiYwyfMGPiEiPiYiIQqvVUqiQNQkJSQYx168F89df96lY8S38/S/ql9+9+wc+x0/TslVjrgReN24xTwgPi6REiccXIDs7OxIRGZ0lpmQJJ8LDI9FqtRQuXIiEhETCwrOuG5mpO/vuu83w979ITKYL7jJ/v3z5OnbsWGWMsp4rIjwK50wdfidne6Ke2J+REVH6ev7en4mJ6fszOTn93wsBlwkNuU3ZcmU4738JgPkLp3EzOJQlP5m+rueJjojFwenx2YHijnbERMU9Zw1DBQrm54e1c/lh9lIunrtsjBRfCXu7YgYXeEbHxmFXzPAMXvFitiycnj5z8v79B3gd+x3rgukfsAb26sbAXukX442ZOpfSJQwvzhemFRMZi71Tcf1je0c74rL5vK1aoxKudarStbc7+Qvkw8LSkgd/PeCHGea73uVZ4iLjsHN6fEbAzrEYCU95/3yaBm0acNX/Kg/vPwTg7OGzvF39bS6evmSUXHMCmXNuZIqiNAVaAvVUVa0G+AN5nwwDVmV00l1VVX1LVdUpGWMp6uOPl2nAIwBVVdMw/BDy5J402Z6NPH8TmzIOFC5ph8ZSS0W3utw4aDiPsajL4zfNcs1dSQxNP+W+7v1p/NRwOD81HI7vigOc/HFXjjwwBwg+H4RDGUfsShZHa2lBPbeG+B08YxDjUqkM/WcOZm6/GdyLv6tfbuNgi2VGN7lAoQK8VfNtIoMjyCn8/C7wRlkXSpcugaWlJV26dsBjr5dBjMfeQ3zYI/1CHffObTmaMaWhdOkS+u5byZJOlH/zDW7dDsO2mA2FC6fPCc2bNw9NmzUg6NpNE1aV7qxvAOXKlcHFpSSWlpZ079aJPXs8DWL27PHk44/fB6BLl/YcPnJCv7x7t05YWVnh4lKScuXKcOasv3697t3ds0xpcXB4/Ebr3qktly9fM1Zpz+R/7iJlyrpQKmN/ur/Xnv0e3gYx+z286f5Res/Azb0NPsdOAWBrWxSNJv0ltLRLCd4o68Kt0PRTyGMnDKNQ4YKM/yrnXct+OeAKpd4ogXMpRywsLXjXvSVHPX2yta6FpQULfp3F7t/2cXD3YSNn+u9Ufrs8t8MiCIuIIiUlhX2HjtOsgeG1L4lJ9/Tz6n9Zt4XO7VoC6dOXku7eA+BacAjXg0Op/8Q1FMK0AgOuUqpMCZxKpj9vW3VqwTHPE9lad+KQabjVep9OdbqzcOpiPLYcyJEH5gDXzl/D2cUJh5L2WFha0KRjE04ePJWtdWMiYqhSpwoarQathZaqdau89tNaXlc5qXNeGEhUVfW+oihvA3UzlqcoimKpqmoKcAjYqSjKAlVVYxRFsQGsVVW99ayNPkWrjPUeAO7AJ6+yiOdRdWl4TlpF99VjULQaLmw+SlxQOI1GdCHyQgg3vM5Ro3drSjesRFqKjof3/mLviJz5AvI8abo0Vk76hbGrJ6PRajmy2YuwoDt0HfEhIRdu4Od1lo/G9SFv/rx8sXgMAPERscztPwPnciXoOaEvqqqiKAp7lu7kzrWX2b3GpdPpGD1yCtt3rkKr1bBm9W9cvRLE+AnDOHfuIvs8DrF61SaWLptPwAVvEhPv0rf3UADq1a/J8BGfkZKaSlpaGiOGTSIhPpFKld/m56Vz0Gq1aDQK27d6sH+/9wsyMU5tXwybwN6969FqNKxctYnAwOtMnjwKP7/z7NlzkBW/bmTlykVcCfQhMTGJHj0HAxAYeJ3ftuzmwvnDpOp0DP1ivP6gJ1++vLRs0ZjBg780+HmzZk6gWrWKqKpK6K2wLOOmqnnsqKls3rYMjVbLhrVbuXb1Bl+OG0qA/yUO7PNm3ZotLF46hzP+niQm3mXAJ+l3aqnXoBZfjhtKaqqOtDQdo4ZPJinxLo5O9owYPYjr14LxPpY+XWv5L2tZuzrrrfzMQafTMXPcfH7asACNVsuODXsIvhbC4DH9uRxwlaOePlRyrcCCFTMpVMSaJq0aMnh0P95r0pM2HVvwTl1XChctRMfu6bdznfTFdK5dfpXT/14NCwst44YNZOCoKejS0ujcriXlypTih+XrqPRWOZo1rMPZgIt8t2Q1iqJQo1olJgxPv91gaqqOXkPGAlCwQD5mTRiBhUXunNYyevIszvpfICnpHi3cezK438d0cct5t6h9EZ1Ox7fjv2PR+rlotRp2bfTg5vVQBo7+hCvnr3HM8wQVq73Nt8u/oVARaxq2qs/AUZ/QvVlvc6f+UtJ0afwwcTEz1k5Ho9VwYJMnt67fotfIj7l+IYhTB0/xZrU3mfzLRKwLW1O3ZR0+HvExA1oO5PheH1zru7L04M+oqorvUT9OeZ1+8Q/NxV7X+5wrOWW+oKIoeYAdgDNwDbADpgBtgY7AuYx5592BsaR3/VOA/6mqekpRlD9VVS2Ysa0pwJ+qqs7NePynqqoFFUXpA7QjfX56OWC9qqpfPy+vVzmtJSc7T867FZox7I17fW8pldmDlJx/bcKrUCRfQXOnYBJO+bJ3QVhu53v+V3OnYBpaS3NnYDL1q/YxdwpGV1Sb+26x+U953tmfo26h1tuli1GP0VaFbjVLvTmmc66q6iPSD8SfdAT4MlPcJmDTU9YvmOn7Kc8aA2JUVR3yL9MVQgghhBBmlJZDGsyvWo6Zcy6EEEIIIcR/XY7pnJuCqqorgZVmTkMIIYQQQvxLr2ffXDrnQgghhBBC5Bj/qc65EEIIIYR4PaS9pr1z6ZwLIYQQQgiRQ0jnXAghhBBC5Dqv618IlYNzIYQQQgiR67yuf4RIprUIIYQQQgiRQ0jnXAghhBBC5DpyQagQQgghhBDCqKRzLoQQQgghcp3X9YJQ6ZwLIYQQQgiRQ0jnXAghhBBC5DpytxYhhBBCCCGEUUnnXAghhBBC5DqqKnPOhRBCCCGEEEYkB+dCCCGEECLXSUM16ld2KIryrqIo1xRFuaEoyldPGR+hKEqgoigXFEU5pChK6RdtUw7OhRBCCCGEeEmKomiBH4G2QEXgQ0VRKj4R5g/UVFW1KrAF+PZF25U55y9wUk0ydwomYaVozZ2CSSTrUs2dgkkUyVfQ3CmYxP2UR+ZOwST2V8lj7hRMona1T8ydgkmcubTG3CmYzO8XVpo7BZMYUHO0uVP4T8oBd2upDdxQVfUmgKIoG4FOQODfAaqqHs4Ufwro+aKNysG5EEIIYUL1q/Yxdwom8V85MBevL0VRBgADMi1aqqrq0kyPnYE7mR6HAXWes8l+wL4X/Vw5OBdCCCGEELmOsf9CaMaB+NLnhChPW+2pgYrSE6gJNHnRz5WDcyGEEEIIIV5eGFAy0+MSQMSTQYqitATGA01UVX3hfEw5OBdCCCGEELlOdu+oYkRngfKKopQBwoEPgI8yByiKUh1YAryrqmpMdjYqd2sRQgghhBDiJamqmgoMAQ4AV4DNqqpeVhRlqqIoHTPC5gAFgd8URQlQFGXXi7YrnXMhhBBCCJHr5IS/EKqqqgfg8cSySZm+b/my25TOuRBCCCGEEDmEdM6FEEIIIUSukwPuc24UcnAuhBBCCCFyHWPfStFcZFqLEEIIIYQQOYR0zoUQQgghRK6TA26laBTSORdCCCGEECKHkM65EEIIIYTIdXLCrRSNQTrnQgghhBBC5BDSORdCCCGEELmOzDkXQgghhBBCGJV0zoUQQgghRK4j9zkXQgghhBBCGJV0zoUQQgghRK6TJndrEUIIIYQQQhiTHJybWPUm77D48M/8fGwpXQZ3zTLesb87PxxazMID3zN1w3TsnO30Y5NXf826ixuZ8OskU6b8j7g2qc5C78V8f/Rn3Ad1yTLeoX9HFnj9wNz9C5m0firFMup0qViG6dtnM//g98zdv5D6HRqaOvUXatWqCRcuHOby5WOMGjU4y7iVlRVr1vzI5cvHOHZsJ6VLlwDAxqYIBw5sJC7uCgsWTDVYx9LSkh9/nMXFi0c4f94bd/e2JqnleZq3aMRJ3/2c8fdk6PBPs4xbWVnyy68LOOPvyf5DmylZyhmAkqWcuR11nsPHd3D4+A7mLPgagHz58rJ+8xJ+P7uP46f2MHHKSJPW8yytWjXBP+AQFy4eYeTIQVnGraysWLX6By5cPMKRozsoVSp9fzZv3hCfE7s5c2Y/Pid206RJvSzrbv7tF86ePWD0Gl5Wnjq1sFu/CruNaynQ88Ms4/natqH47u0U+/UXiv36C/k6tNOPWQ8aQLHVKyi2egV5mzczZdovrX6zOmz32cDOk5voO6RnlvF36lZjvecKzoYdpWWHpvrljiXsWXdgORu9VrLl6Fq69nI3YdYvr17T2mw5vpZtJ9bTe0iPLOPV61RjzYFlnLztTfP2TbKMFyiYn71+Wxk9fZgp0jWKCTPm07j9B7j3/MzcqfxrlZu4MuPQImYd+YF2gzpnGW/dz41vDn7H1H3zGb1uMraZjhOWB2/ma4+5fO0xl6G/fGXKtM1CNfKXueS6aS2KorgAe1RVrWzmVF6aRqNh4DeDmNxjAvGR8czdvYAzB09zJ+iOPibkcjAj2g8n+eEj3u3Zlj7j+jLnf98CsH3JNvLky0ObHu+aq4Rs0Wg09Js2kGk9JpMQFc/MXXPx9TpDmEGdIXzZYQTJD5Np3fNdPh7bhwVD5vDowSO+H/4dUaGRFC1uw+y98wg45s/9e3+ZsaLHNBoNCxd+Q/v2PQgLi+TEid3s2XOQq1eD9DF9+nQnKekulSo15v333fjmm7F8/PH/ePjwEV9/PY+KFd+iUqU3Dbb71VefExsbR5UqTVEUBRubIqYuzYBGo2HWvEm8796XiPBoPA9vYb+HN9evBetjevR6n6Ske9Su3hr3Lu2Y9PUoPu07HIDQkNs0a5T1gObH71dw4vhpLC0t2bZrJS1aNuaQ1zGT1fUkjUbD/AVTcevQk/DwKI4f38XevQe5evWGPqZ3n24kJd2lapWmdO3qxrRvvqJ3ryHExyfStWs/oiJjqFjxTXbuWk35cnX163Xs1Ia//rxvjrKeT6Oh0IgvSBg+Gl1MLMWW/cwjn99JDb1lEPbQ+zD3FiwyWJanXl0s3yxPXN/+KJZW2PzwHY9OnUa9n/Pq1Gg0fDVzJIO6DSM6MoZ1+5dx1NOHm9dD9TGR4dFM/mI6vQYbfkCJjY6nj9tnpCSnkC9/PrYcXcPRAz7ERseZuIoX02g0jJkxnCEfjCA6MpZVHks5dsCHkKDH+zMqPJqvh82g52cfPHUbn43pz7lTAaZK2Sjc27Xioy4dGTdtrrlT+VcUjYaPp37K3J5TSYiKZ9Ku2QQcPEvEjTB9zO3AEKa6jSH5YTLNerah29iP+WnIfACSHyYzud0oc6UvXhHpnJtQedc3iQqNJPp2NKkpqRzffYzaresaxFw8eZHkh48AuOZ/DVvHYvqxCyfO8+DPBybN+Z8o51qeqNAoYu6k13li93FqtqptEHP55EWSHyYDcN3/GjaOtgBEhkQQFRoJQGJMAnfj7lLIppBpC3iOWrVcCQ4OJSTkNikpKfz2227c3FobxLi5tWbt2i0AbNvmQbNmDQC4f/8Bv/9+lkePHmbZbu/e3fj22x+B9L94Fh+faORKnu+dGlUJvXmLW6FhpKSksGPbXtq2b2EQ07Zdczat3w7A7h0HaPSUznFmDx485MTx0wCkpKRw4Xwgjs72xikgm2rWdOVm8C1CQ++QkpLCli276dDBcH92aN+adWu3ArB9uwdNm9YH4Pz5y0RFxgAQGHidPHnyYGVlBUCBAvn5/PP+zJ79vQmryR7LCm+jC4tAFxEJqak88PImT8MG2VrXwqU0yQHnQZeG+vAhqTeCyVO39otXNIPK1StwJySM8NsRpKakcmDHIZq2aWQQE3kniqArwaSlGfbIUlNSSUlOAcAqjyWKopgs75dVqXoF7oSGE347ktSUVA7uPESTNoZnHCPDorhx5SZqWtZe4NtV3sTGriinj541VcpGUdO1CoULWZs7jX/tDddyxNyKIvZONLqUVM7s9qF661oGMVdPXtK/fwb7X6eog605Us0R0lCN+mUuufXgXKsoyi+KolxWFMVTUZR8iqIcURSlJoCiKMUURQnN+L6Poig7FEXZrShKiKIoQxRFGaEoir+iKKcURbExVdK2DrbERcTqH8dHxmFr/+xfqlbdW+N32M8Uqb1SNg62xEc+7jAlRMZj+5wXjxbdW+F/JGud5aqVx8LKguhbUUbJ859wcnIgLCxC/zg8PBInJ/tnxuh0Ou7d+wNb26LP3GbhwukfPiZPHsXJk3tZt+4nihcv9sx4U3B0sic8/PH/e0R4NI6OhnU6ONoTHp7+QervOm1s0ussVboE3se3s3PvGurWq5Fl+4UKW9O6bTOOHz1pxCpezMnJnrBww/3pmGV/Po551v50d2/LhfOXSU5Of8OcNGkkixYt4/79rB/EzE1rVwxdTIz+cVpsLFq7rM+3vE0aU2zlMopMm4KmePpp85QbweSpUwfy5EEpXAird1zRFrfLsm5OUNzRjuiIx3VGR8Zg55j9XO2dirPJexX7/Laz8sd1ObJrDmDnUOyJOmOzXaeiKAyb/D8WTfvJWOmJl1TU3oaEiMzvnwkUfc5xQuNuLbh45Jz+sWUeKybtms2E7TOp3jpnfnAWL5ZbD87LAz+qqloJSAKyTmo2VBn4CKgNTAfuq6paHTgJ9HoyWFGUAYqi+CqK4hv65+1Xl/VTmi/qM640btK5KeWqlmP7kq2v7ueb0bPqbNS5CW9UKceuJdsNlhcpXpTPFwxn8ahFz1zXHJ7WQXsyv+zEZGZhoaVECSdOnvSlXr32nD7tx6xZE/59sv/Cv6kzOiqG6pWa0bxRZyaOn8XPy+ZR0LqAPkar1bJ0+XyW/byGW6FhWbZhStnaVy+IqVChPNO++YrPPx8HQNWqFXmjbGl278p5c82Bp9bDEzU/PHGSmPc/JK5Pf5J9/SgyPn3uavJZXx6dOkWxn3+g6JSJpFwKRNWlmSLrl5eNOp8nOiKG7s1706led9y6tcWm2LM/YJvTy77eZNa1T2dOeJ8yOLgXZvYS+7Oee2NcqpZl39Kd+mWj6g9kascvWTL0Oz6a1Be7UuY9O2ls0jnPWUJUVf17gpwf4PKC+MOqqv6hqmoscBfYnbH84tPWVVV1qaqqNVVVrelSsNQrShniI+Mp5vS4o2HrWIyEmIQscdUaVuP9Id2Z3m8aqcmpr+znm0pCVLzBdBwbR1sSorPWWaVBNd4b8j6z+083qDNfwXyM/XUiG+auJcj/uklyzq7w8EhKlHDSP3Z2diQyMuaZMVqtlkKFrElISHrmNuPjE/nrr/vs3LkfgG3b9uLqat5LKiLCo3B2dtA/dnK2JyrKsM7IiCicnR2Bx3UmJiaRnJxCYmJ6vRcCLhMacpuy5cro15u/cBo3g0NZ8tMqE1TyfOHhUZRwNtyfUU/sz4hMMU/uTydnBzZsXMKn/UcQEpL+Qb52nXeoXr0KgVd88Dr0G+XKl2Hf/o0mqujFdDGxaIsX1z/W2Nmhi4s3iFHv3YOU9Gkd93fvxfKtx9dI/Ll6HXF9PyVh+GhQFHR3zPsB61liImKwd3pcp71jcWKjXr77HRsdR/C1EN6pW+1VpvfKxETGPlGnHXHZrLNqjUp06/seO09v4otJg2nXtQ1Dxg00VqoiGxKj4rFxyvz+aUPSU44TKjaoSochXVjYf6bB+2dSTPqUyNg70Vw9dZnSlcpkWVfkfLn14PxRpu91pF/YmsrjevI+Jz4t0+M0THhRbND56ziWcaJ4SXssLC1o5NaYMwdPG8SUqfQGg2YOYXq/adyNv2uq1F6pG+eDcCzjSPGSxbGwtKCBWyN8D54xiHGpVIYBMwcxu9907mWq08LSgtFLx3J062FOefxu6tRfyNf3POXKlcHFpSSWlpa8/74be/YcNIjZs+cgPXum34nnvffaceTIi+vYu9dLf7ePZs0acOVK0AvWMC7/cxcpU9aFUqVLYGlpift77dnv4W0Qs9/Dm+4fpd9JwM29DT7HTgFga1sUjSb9V7G0SwneKOvCrdD0i4HHThhGocIFGf/VDBNW82x+fucpW86F0hl1du3qxt69hvtzr8dBevRMPznXuXM7jh5N35+FCxdi29ZfmTzpW06dejwta9kvaylXtg4VKzSkZYv3uREUQtt3n34hnjmkXL2KtqQzWkcHsLAgX8vmPDph+BzV2D6e7ZenYX1Sb2WcQdRoUAqlT8OyKPsGFmXf4NHZnDlX+XLAVUq9UQKnUo5YWFrQxr0FRzx9srVucUc78uRNv37AurA1rrWqEHrjFZ5FfYUCA65SqkwJnEqm19mqUwuOeZ7I1roTh0zDrdb7dKrTnYVTF+Ox5QA/zFhi5IzF84Scv0FxF0eKlSiO1tKC2m4N8T/oaxBTqlIZes8YyKL+s/gj/p5+ef5CBbCwSj+kKVjUmvI13iYiKGd+eH5VVFU16pe55Lq7tTxHKFADOANkvUdhDpCmS2PpxJ+ZsmYqGq2GQ5sOcuf6bT4a0YMbF4M4c/AMfcd/Qr78eRnzU/pp5LiIWKb3mwbAjC2zKVG2BHkL5GX56ZX8MHoR/sfOPe9HmkWaLo3lk5YyfvUUNFoNhzcfIizoDt1HfETwhRv4ep3h43F9yZs/HyMXjwEgLiKO2f2nU69DAyrUroR1EWuadW0OwI+jFhEaGGLOkvR0Oh3Dhk1k9+41aLVaVq3axJUr15k0aQR+fhfZu/cgK1duYsWK77h8+RgJCUn06jVEv/61ayewtrbGysoSN7c2dOjQk6tXg5gwYSYrVnzHnDmTiYtLYMAA895mUKfTMXbUVDZvW4ZGq2XD2q1cu3qDL8cNJcD/Egf2ebNuzRYWL53DGX9PEhPvMuCT9Du11GtQiy/HDSU1VUdamo5RwyeTlHgXRyd7RowexPVrwXgfS5/GtPyXtaxdvcWsdY4cMYmdu1aj1WpZvXozV64EMWHicM6du4jHXi9WrdzMsuXzuXDxCImJSfTu9TkAAz/rxRtlS/PV2KF8NXYoAB3dPiY2Nv55P9L8dGncm78Im/nfgkbDg737SA0JpWC/vqRcvcajE79ToOt76ReJ6nSk3btH0vRZ6etaaLH9cSEA6v37JE2dDjl0WotOp2P2uAUs3jAfjVbLzg17uHkthEFj+hMYcJWjnj5UdH2b+StmUqiINY1bNeCz0f3p2qQnZcq7MGLKkPRpMIrC6p82cOPqTXOX9FQ6nY5vx3/HovVz0Wo17Nrowc3roQwc/QlXzl/jmOcJKlZ7m2+Xf0OhItY0bFWfgaM+oXuz3uZO/ZUaPXkWZ/0vkJR0jxbuPRnc72O6uLUxd1ovLU2XxrpJyxi5eiIarYbjm72JCLqD+/APCL14gwAvX7qN7UWe/HkZvDj9fSI+PI5Fn87CqVwJes8YSJqqolEU9v603eAuLyL3UHLSfN7sePJWioqijAIKAhuBzcCfgDfQU1VVF0VR+gA1VVUdkhEfmvE47smxp+lUqkPu+g/6h6wUrblTMInd0f7mTsEkrPPkM3cKJnE/5dGLg14DN975b5yabncj2dwpmISF5r/xevv7hZXmTsFkBtQcbe4UTOLX0K056tZFtZ2aGPUY7UzEUbPUm+s656qqhpJ+geffjzPf1LRqpu8nZIyvBFZminfJ9L3BmBBCCCGEyB1Us/6pIOPJrXPOhRBCCCGEeO3kus65EEIIIYQQuW1qdnZJ51wIIYQQQogcQjrnQgghhBAi1zHnHwoyJumcCyGEEEIIkUNI51wIIYQQQuQ6MudcCCGEEEIIYVTSORdCCCGEELmOzDkXQgghhBBCGJV0zoUQQgghRK4jfyFUCCGEEEIIYVTSORdCCCGEELlOmtytRQghhBBCCGFM0jkXQgghhBC5jsw5F0IIIYQQQhiVdM6FEEIIIUSuI3POhRBCCCGEEEYlnXMhhBBCCJHrvK5zzuXg/AXyK/+N/6KHqs7cKZiELu2/Uee9R/fNnYJJKCjmTsEkKgbcMXcKJlG5cGlzp2AS+TSW5k5BvGJLfeeYOwXxGvlvHHkKIYQQwqQG1Bxt7hRMQg7MzUfmnAshhBBCCCGMSjrnQgghhBAi15E550IIIYQQQuQQMq1FCCGEEEIIYVTSORdCCCGEELnO6zqtRTrnQgghhBBC5BDSORdCCCGEELmOqqaZOwWjkM65EEIIIYQQOYR0zoUQQgghRK6TJnPOhRBCCCGEEMYknXMhhBBCCJHrqHKfcyGEEEIIIYQxSedcCCGEEELkOjLnXAghhBBCCGFU0jkXQgghhBC5jsw5F0IIIYQQQhiVdM6FEEIIIUSukyadcyGEEEIIIYQxSedcCCGEEELkOqrcrUW8CtWaVGee948sOPoTHQe9l2W8Xf+OzPH6ntn7v2P8+qkUc7YDoJizHdP3zGOmxwLmHFxEyx5tTJ36S6ne5B1+OPwTi48t4b3BXbOMd+zfiUWHfmTBgUV8veEb7DLqBJi4egprL25g/K+TTJnyc7Vu3ZRLl45xJdCH0aP/l2XcysqKdet+4kqgDyd8dlO6dAn92JgxQ7gS6MOlS8do1aqJfnnhwoXYuHEpFy8e5cKFI9StUwOAKVNGc87vIL5nPfHYux5HR3vjF/gUrVs15eKFIwRePs6oUYOzjFtZWbF2zWICLx/n+LFd+pptbIpw4MAm4uOu8t2CaU/d9tYtKzjn52XU/LOrVasmXLhwmMuXjz2zzjVrfuTy5WMcO7bziTo3Ehd3hQULphqs07WrG2fPHuDcOS+mTx9nkjpeRouWjTlzzhO/84cYNmJg4wjkCgAAH6pJREFUlnErKyuWr1qI3/lDHDy8hZKlnA3GS5Rw5E7UeYYM7WeqlP+R2k1rse7YSjb4rKbH/z7IMl6tThWW7/+Zw7c8adq+scFYcafizFs/mzVHVrDm8AocSpjn9zA7ajatwfIjy/j1+Aq6D+6WZbxKncr86PED+0L20qhdQ4Ox/uP6sdRrCcu8lzL460GmSvkfqdzElRmHFjHryA+0G9Q5y3jrfm58c/A7pu6bz+j/t3fe4VUVWx9+V0KQKl0JIISOIhAuTRCRJl6BACpFpIugohcVsSBIk6KfiIhXEfACXlQE7JQrTekgEDpSQgk1dAIiPZnvjz0J5yQnJMGcQlzv8+Rhzuw1s9dvT9mzZ2ZvvhxEAZf7yn/2zGDI3FEMmTuK3hPf8KXbGcqAEaOp1+wJWnV81t+uKF4kwwfnIjJXRPKmwz5MRLZmtB9pPPd5n54vKIhubz/Du12G0rfxv6jT4gGKli3mZhO9bS/9m7/C6/98id/mruTJfl0AOHP8DIMee51+TV9mQMvXaPHc4+S7I58v3U8zQUFB9Bz2LG93GUzvRs9Tt0U9ipW9y81m77a99G3Wh5cf7s3KOSvo/Ga3xGM/jP+OMS+P9rXbKRIUFMTYD4cTEdGRylUa8ES7Vtx9d1k3m6e6tSf2zFnuvqcuH46dyIgR/QG4++6ytGvbkirhDWnevAMfjR1BUJDT7D4YPZT5836lUqUHqVbtIbbviALg/ffH8Y9qD1G9RhPmzl3IgP4v+1YwjuYPPxxGi5adqRLekHZtW1Khgrvmbl2fIDY2lnsqPsDYjz5j+DBnEHrp0mWGDBnFG28M85h3y5b/5Pyff3pdQ1pI0NmyZRfCwxvRtm2LZDq7dm1HbOxZKlasx0cffcawYf2ABJ3v88Ybw93s8+fPy8iRb/LII+35xz8ac+edBWnQ4H6faUqNoKAg3hs9mDaPdee+6v/k8TbNKV+hjJtNpy5tOBt7lmpVGjHu48kMfvs1t+PD3+3PwgVLfel2ugkKCqLP8N707diPTg2eonGrhoSVLeFmc+zwcUa8/H8s/GFRsvQDPnydaeNm0Kn+U/Rs1oszJ2N95Xq6CAoK4oVhz9O/8wB6NOxJ/Zb1KV62uJvN8cMnGNXnfX754Ve3+Huq3U3F6vfwbJPn6Nn4WcpVKUfl+yr70v00I0FBdBragw+6Dqf/Qy9Rq0VdipRxv38e+H0fQyNeY+AjfVj3v9W07dcp8diVS1cY1LQvg5r2ZWyPd3ztfobRqulDfDrac9/6d8QY49U/f5Hhg3NjTFNjTGD2Yn6mTHhZjkbHcPzgMeKuXmPVrOVUf6iWm83vq7Zy5dIVAHZv2En+0AIAxF29xrUr1wAIyRqCBIlvnU8HZcPLEhMdw7EDx7h29RrLZy2lZhN3nVtXbeHKpcsA7NqwkwJWJ8CWFZu5eP6iT32+ETVrVGXPnmj27TvA1atXmT7jRyIi3FcuIiKaMHXqTAC+/XYODRvUtfEPM33Gj1y5coXo6IPs2RNNzRpVyZ07F3Xr1mLS5GkAXL16lbNnzwHwxx/Xnxlz5Mzhlw6iRo1wN80zZv5EREQTN5uIiCZM/eIbAL77bk7iAPTChYusXLmWS5cvJ8s3Z84cvPhiD0aOHOt9EWkgqc6ZM2d51PlFos65yXRevnzJzb5kyeJERe3j5MnTAPzyy3JatXrEB2rSRrXqVdi7dz/7ow9y9epVvvtmDk2bNXazeaRZY6Z9+T0AP37/Mw/Wr514rGnzxuzfd5Ad26N86nd6ubtqBQ5HHybmQAzXrl5j0Y+/UvfhOm42Rw8dY8/2vZh49zYWVrYEwVmCWbcsEoCLFy5x+VLy+hwIlA8vz5HoGI4eOMq1q9dY8tMS6jSp7WZz7NAx9u3Yl6wvMQay3paVLFmzEJI1hCwhwZw5ecaX7qeZUuFlOL7/KCfs/XPNrOVUbVLDzWaHy/1zz4Zd5CtcwFNWtzTVwyuR5/bc/nZD8TLpHpyLyGsi0tuGPxCRX2y4kYh8ISLRIlLQzohvF5GJIrJNROaLSHZrW01ENonIKuB5l7wrisgaEdkoIptFpKzNZ4eIfG7jvhGRHC75LBGRSBGZJyKhNr60iPxs45eJSAUbX1JEVonIWhHxvN7uRfIVzs+pmJOJv0/FnCJf4fwp2tdv15hNi9cn/s4fWpB3fx7Dv1d/xk+ffseZ44HZieYvXICTR9x1Frgz5U6ycbuHWP9rpC9cuymKFC3MoUNHEn8fPhxD0SKFk9kctDZxcXGcPXuOAgXyUbRI8rRFihamVKkSnDx5iv989gFr18xj/KfvkSNH9kS7oUNfZ++etbRv/yiDh7znZYXJKVLkup4Ev5NpdtEWFxfHuXN/UKDAjVdzBg96lTFjJnLxYmA8fBXxVD5F7kzRJi069+zZT7lypSlRohjBwcFERDShWLEi3hFwE4QWuZPDh2ISfx85fJTQZJqv28TFxXHu7HnyF8hHjhzZefHlZ3h35Ec+9flmKFS4IMePnEj8fSLmBAULF0xT2rtKFeP8uT8ZNnEw/5n3Kb0G9Exc8Qo0ChYuwAk3nScpkMZB6fb129m4ahNfr/uKryO/Yt2SSA7uPugtV/8S+e7Mz2mX+8rpmNPku8F9pV7bRmxxuX+G3JaVgT+9y4DvR1K1SU2v+qr4jniMV//8xc30NkuBB2y4OpBLREKAusCyJLZlgY+NMRWBWOBxGz8Z6G2MqZ3E/lngQ2NMuM37kI0vD0wwxlQGzgG97Dk/AlobY6oBk4CE9eUJwL9sfF/gExv/ITDOGFMDOJqSQBHpKSLrRGTd7vPRqV6QtCJ4mO1OoezrPvogpSqVYdb47xPjTsec5PV/vsTL9Z6l3uMNyFMwT4b5lpGIJNeZ0uzvg4/Wp3TlMvww/jtvu3XTpEWPZ5uU02YJDqZq1UqMH/9fatR8mD//vMBrr72QaDNw4LuUKl2DadO+p1evbsny8DZp05w83Y1m+StXvofSpUvw008//2X/MoqbL9uUdcbGnqV37/5MnfoxixZ9w/79h7h27dpfdzaDSJOeFGze6P8i4z6ezJ9/XvCWexmHp8XFNK5CBWcJpnLNe/n47fH0bNqL0OKhPNI2QN/zSWf9dKVIWCjFyxTnyZodaV+jA+F1wqlU696M9jBjSIfO2q3qEVa5NP+b8GNiXN86zzC0xeuM7z2GJwd2o1DxwH2HQEk7uq3lOpFANRHJDVwGVuEMpB8g+eB8nzFmo0u6MBHJA+Q1xiyx8VNd7FcBb4rI60AJY0zC9NpBY8wKG/4C50GgPHAvsEBENgIDgGIikguoA8y08eOBUJv2fmCah/O6YYyZYIypboypXiZXWOpXJI2cPnqKAqHXZ24KhBbgzLHTyezuvb8yrV5ozainRyRuZXHlzPEzHNp1kPI178kw3zKSUzEnKVjEXefp48l1Vq5bhdYvtGVk92EedQYKhw/FuM18Fi0aypGYY8ls7rI2wcHB5MlzO6dPn+HQ4eRpY44c49DhGA4dimHN2g0AfPvdHKqGV0p27q+//p5HH23qDVk35PDh63ogBc2HjyZqCw4O5vbbc3P6dMo72u6rVY2qVSuzc+dKfln0HWXLlmT+/BneEZBGDnsqn5jjKdqkRSfA3LkLqVevJfXrP0pU1F52747OcN9vliOHj1K0WGji7yJFC3M0iWZXm+DgYG7Pk4szp2OpXqMKQ95+jU3bFvNcr6706fscPZ7pRCByIuYkdxS5/kJgodBCnDx2Kk1pj8ecIGrrbmIOxBAXF8/yeSsoV6ls6gn9wMmYkxRy01mQ0x7uK564/+H72bFhB5cuXOLShUus/XUtFapW8Jarf4kzR0+R3+W+kj80P7Ee7iv33F+Z5i88zodPj3S7r8TaleYTB4+xY/U2SlQs6X2nFeUmSffg3BhzFYgGugErcQbkDYDSwPYk5q6b9OJwPt0opDBfbIz5CmgBXATmiUjDhENJTW0+24wx4favkjGmidUU6xIfboy5O0lav7BnUxSFS4ZS6K47CA7JQu2IukQuWONmE1axJE+P7MWo7iM4d+psYnz+wgUIuS0rADlvz0n56hWI2XOEQCRqUxShJYtwx113kiUkC3Uj6rE2ic6SFUvx3MjnGdH9bc666AxE1q7bSJkyJQkLu4uQkBDatW3J7Nnz3Wxmz55Pp05tAHj88Wb8unhFYny7ti3JmjUrYWF3UaZMSdas3cCxYyc4dOgI5cqVBqBhw7ps374LgDJlrt80Ipo3YefOPb6Q6ca6dZsoUyYsUXPbNi2YPXuBm83s2Qvo1NH5Es9jjzVj8eIVnrJKZMLEqZQsVZ3y5evQsNFjREXto0mT5F+W8CWOzutl26ZNhEedHRN1NmXx4pWp5luokLPcnjdvHnr27MTkydNSSeE71kdupnTpEhQvUYyQkBAea92M/811fyHy57mLaN/B+RpGy0f/ydIlqwFo2qQ9VSrWp0rF+oz7ZAqjR41j4vgU5zn8yo6NOyhWsiihdxUmS0gWGrVswPL5qZedk3YnufPmJm9+Z3XyH/dXJXrXfm+6e9Ps3LSTomFFKGz72wdbPMiqBavTlPb4keNUqlWJoOAgZ7XgvkoBu61l36bd3BEWSsFizv2zZkRdNixY52ZTvGJJuox4hrFPv8Mfp84lxue4PSdZsjpfjs6VLzdlq1XgSNQhlFufeGO8+ucvbvY750txtos8BWwBRgORxhjjacnUFWNMrIicFZG6xpjlQIeEYyJSCthrjBlrw5WBvUBxEaltjFkFtAeWAzuBQgnxdptLOWPMNhHZJyJtjDEzxXGosjFmE7ACeAJn9r0DPiY+Lp4pAyfS77+DCAoOZvGMhRyKOkjrPu3Zt3k3kQvX8uSbXcmWIxsvfuJ8HeHUkROMenoERcsUo+OAbhhjEBFmT/iRgzsD82YRHxfPxLc+ZdDUIQQFB7Fo+kIO7jpA+z4d2L0lirUL1tClfzey5cjGq+OcT1qdOHKCkd2dN9CHf/MORUsXI1vObEz8bTIfvzqWjUs3+E1PXFwcL740gDlzviI4KIgpn0/n9993MWhQXyIjNzF79gImTf6aKVPGsv335Zw5E0uHjs4n+X7/fRczv5nF5k2/ci0ujt4v9ic+Ph6Al15+i/9+/hFZs4awd98Bnn66j6N/eD/KlSuNiY9n/4HDPP+87z/7FRcXx0svvcXsWV8QHBzMlM+ns337LgYOfIX1kZuZPWcBk6d8zeRJY/h92zJOn46lU+frn5jcuXMlt+fOTdasIUREPEyz5h3YsSPwXiBM0Dlr1lSCg4P5PFFnHyIjtzBnzgKmTJnOpElj2LZtKadPx9K58/XtRzt3riC3i87mzTuyY0cU778/mEqVnJWtESPGsHv3Pn9JTEZcXByvvTKEb3+YTHBwMF9OncmO7VH0G/AiG9dv5X9zFzH18xl8+tn7RG5axJkzsXTv+pK/3U43cXHxfDDgI97/6l2CgoKYM/1/RO/aT/e+XdmxaScrFqyiQpXyDP/PEHLnyUWdh2rz1Ctd6NywO/Hx8Xw8dDxjpo8CgV1bopj11Rx/S/JIfFw8/37rE0Z8MZyg4CDmTZ/P/l376fxKJ3ZtjmL1gtWUq1KOQRPfInee3NzXuBad+nSiZ+NnWDZnOeF1wpmw4FOMMaxbEsnqhb/5W5JH4uPi+XLgZ7zy37cICg5i2YxfOBJ1kFYvP0H0lt1sXLiOtv06c1uObPT65BUATh0+ydge71CkTDG6jHiGeGMIEmHOuO85svvWHJy/Ougd1m7YTGzsORq16kiv7p14PCJAt1wpN43czJ4aEWkE/IyzPeVPEdkFfGqMGS0i0di96MBsY8y9Nk1fIJcxZrCIJOwRvwDMw9k3fq+I9AM6Aldx9oQ/CdwOzMV5IKgDRAGdjDEXRCQcGAvkwXnQGGOMmSgiJYFxONtZQoCvjTFDbfxX1vZbYIAxJteNtLYv0SpzfuE+CZdMnL9d8Amzj65P3SgTEKgvr2U0Ht/jyIRkz5LV3y74hHvzlEjdKBOQPSjE3y74hKLBOf3tgk+YsM73L+37i5CCpQKq082Xq4xXx2hnzu/2i96bGpz7EhEJw2WQ72t0cJ650MF55kIH55kLHZxnLnRwnvnQwblvuNltLYqiKIqiKIriN/z5uUNvEvCDc2NMNM5XWRRFURRFURQlUxPwg3NFURRFURRFSUqgb82+Wf4eG1MVRVEURVEU5RZAZ84VRVEURVGUWw5/fovcm+jMuaIoiqIoiqIECDpzriiKoiiKotxymEz6tRadOVcURVEURVGUAEFnzhVFURRFUZRbDt1zriiKoiiKoiiKV9GZc0VRFEVRFOWWQ79zriiKoiiKoiiKV9GZc0VRFEVRFOWWQ7/WoiiKoiiKoiiKV9GZc0VRFEVRFOWWI7PuOdfBuaIoiqIoinLLkVkH57qtRVEURVEURVECBJ05VxRFURRFUW45Mue8uc6cK4qiKIqiKErAIJl1v86tjIj0NMZM8Lcf3kZ1Zi5UZ+ZCdWYuVGfm4++k9e+GzpwHJj397YCPUJ2ZC9WZuVCdmQvVmfn4O2n9W6GDc0VRFEVRFEUJEHRwriiKoiiKoigBgg7OA5O/yx4y1Zm5UJ2ZC9WZuVCdmY+/k9a/FfpCqKIoiqIoiqIECDpzriiKoiiKoigBgg7OlYBARPKKSC+X3/VFZLY/fbJ+hInI1nTYTxGR1jb8mYjc48Gmq4j8OyP99CcislhEqqdiE/CaRSRaRAp6iF/p7XP4E1s2RVx+e8VHEZlr27lbW/fCebyafyAiIm/62wdvk96+OFBJaAfpsPebbhE574/zKjo4VwKHvECmuqEaY542xvzubz+U1BGR4JSOGWPq+NIXP9AVKJKaUVoQkRT/12ljTFNjTCzeb+uZri9JA5l+cJ5ZcGkHipIiOjjPYEQkp4jMEZFNIrJVRNqJSDURWSIikSIyT0RCrW0PEVlrbb8VkRw2vo1Nu0lEltq4bCIyWUS2iMgGEWlg47uKyHci8rOIRInI//lRe5iI7LAzxltF5EsRaSwiK6xvNUVksIhMsrOte0Wkt03+DlBaRDaKyHs2LpeIfGPz/FJExE/SgkVkoohsE5H5IpJdRMJFZLWIbBaR70UkX9JErjPKItJNRHaJyBLgfhebCBH5zZbpQhG5U0SC7PUqZG2CRGR3Rs1mishrCdddRD4QkV9suJGIfCEiTURklYisF5GZIpLLHvdYj13yDRKRz0VkmC81p0FPe9tutorIuy7pzovIUBH5DajtEp/dtqceCXb23/q2TJPVSRFpauOWi8hYsas+IlLA1pkNIjIeEJfz/GCv5TYR6WnjuovIBy42PURkdAaV30Bx+putIjJBHFoD1YEvxWl72e1p/mXTbxGRCjZ9TnHa7lqrp6WN72rPMwuYLyKhIrLU5rdVRB6wdgkz8p7aekbilr+IvGp93iwiQ6wvqfZV1m6wiEwVkV9sfA8v+JsuktYbEXkHyG71fmltOorIGhs3XuzDp63z79r0C8XpkxP64hbWpquI/GjbwE4RGeRHuUnx1Be79rMFRSTahrvaazVLRPaJyAsi0sfW3dUikt8bDqahfUZbP8NEZHtSPda2mjj3/1XA8y55V3Qp180iUtalLn9u476R62OJlMYepW35RorIMpc2XlKcvmOtiLztjeujpBFjjP5l4B/wODDR5XceYCVQyP5uB0yy4QIudsOAf9nwFqCoDee1/74CTLbhCsABIBvOrNdee55swH7gLj9pDwOuAZVwHvwigUk4A5KWwA/AYHs9bgMKAqeAEJt2q0te9YGzQDGb1yqgrh81hdvfM4COwGbgQRs3FBhjw1OA1ja8GGfgE2rLqxCQFVgB/Nva5OP6i9lPA+/b8CDgJRtuAnybgZruA2ba8DJgjS2DQcDrwFIgpz3+OjDQHk+pHi+2eU4D+ts4n2lORc8gFz+yAL8AraytAdq65BNty3sh0Nkl/vyN6iROuzsIlLR204DZNjwWGGjDzew5C9rf+e2/2YGtQAEgJ7AHCLHHVgKV/mr5uZ7PhqcCEa71NMl1SOiLegGf2fAIoKMN5wV2WX+7Aodc9LziUg+Cgdwu+RYkSVv3Upvd6lKPJuD0QUHAbKAeaeirbPrBwCZbRgVtORfxdT+URJ+nenPe5fjdwCyXOvQJtj7b+veIDX8PzLd1pwqw0cZ3BWJsvgnnqO4LbWkoV099cWL9tWUU7aJjN5Abp/2fBZ61xz7A9jVe8PNG7fOZJO0gmR4bdr2/vOdSnz8COthwVls+YbZc77fxk4C+3LjPXgSUteFawC82/JNLXXnetV7pn2//dOY849kCNLazEw8AdwH3AgtEZCMwAOfmDnCvfWrdAnQAKtr4FcAUO0uTsNxeF+eGijFmB84gvJw9tsgYc9YYcwn4HSjhVYU3Zp8xZosxJh7YZn0zONclzNrMMcZcNsacBI4Dd6aQ1xpjzCGb10aX9L5mnzFmow1HAqVxHpqW2LjPcW74KVELWGyMOWGMuQJMdzlWDJhn68CrXK8Dk4DONvwUMPmvy0gkEqgmIrmByziDzOrAA8BF4B5gha2vXXDqU3lSrscA43FuIMPtb19qvpGeWBc/rgFfcr2s4oBvk+T1I85D8H9TOJenOlkB2GuM2WdtprnY1wO+ADDGzAHOuBzrLSKbgNU4/URZY8yfOA8Qze1sVogxZks69KZUfgANxFmx2AI05Pp198R3LucKs+EmwBs238U4DyXF7bEFxpjTNrwW6CYig3EeLP64wXm8TRP7twFYj1NWZe2xtPRVAD8aYy7a/upXoKavnE+BZPUmyfFGQDVgrS2rRkApe+wK8LMNbwGWGGOuklzzAmPMKWPMRZy6UNcbQm6CpH1xWCr2vxpj/jDGnMAZnM+y8Un1ZiQ3ap/Lktgm0yMieXC/v0x1sV8FvCkirwMlbPkAHDTGrLDhL3DKy2OfLc5KWh1gpo0fjzOZAs4KZ0L/5XpexcekuD9QuTmMMbtEpBrQFBgJLAC2GWNqezCfgjOLt0lEuuLMzGGMeVZEauHMtG0UkXBclsM9cNklHId/y9XVl3iX3/Fc9yut/gaKrqR+pPllHhdS+mbpR8BoY8xPIlIfZ6YOY8xBETkmIg1xBrodbuKcnh0x5qpd+u2GM7OyGWiA89CxD+fG3N41jYhUIuV6jM2ngYi8bx8SwUeaU9FzAGeg4olLxpi4JHErgEdE5Cs7UEuKpzqZ2narZPlY3Y2B2saYCyKyGGewC/AZzh7iHXh4QLnJ8suGM4Na3V7nwS7n80SCTtd2J8DjxpidSfKuBfzp4t9SEamH039NFZH3bvCw420EGGmMGe8WKRJG2voqSF5+fvv+cCr1JtEM+NwY089DFldd6nWiZmNMvLi/LxAwmpOQtP1lx5l9TphoTHot0lrGGUYq7XP7DfxL0COkcL2NMV+Jsw2vGc4Ex9M4K+eeykvw0GeLyO1ArDEmPCUJNxSo+ASdOc9gxPnqwQVjzBfAKJxBRiERqW2Ph4hIwoxVbiBGREJwGYiISGljzG/GmIHASZzZkaUJNiJSDmfGyu0meYvzB871uBU4C5yxKyMAnYAlN7D/Dagvzv7jEKCNy7E8wGEb7pIk3Wc4syAzPAwi/ypLcZY+l+LM5jyLMxO8GrhfRMoAiEgOW992knI9BvgPMBdnNiYLvtd8Iz0P2j2ewUB7blxWA3G2Wn2SjnPvAErZAR84y8eufiW020dwtvSAcw3O2AFWBZylcACMMb/htPkncZ+FdyW95ZcwaDlpZ85au+SV1rY3D2cvesI++6qejESkBHDcGDMRp178I4mJt9u6a/7zgKfk+r77oiJyRzrzaynOOz8FcCZQ1maYp+knpXpz1bYzcLYstE7QKSL5bZmkh4dsuuxAK5yH1kAlmusP4K1vYOdLPLbPFB743TDOy6JnRSRhtcJ1bFAKZ5VuLM4WlMr2UPGEvhmnj1tOCn22MeYcsE9E2th4EZEqNu0K4Imk51V8jw7OM55KwBq7XNQf52bfGnjXLkVuxFlSAngLZxCzAOcGn8B7Yl9gw2ncm3AGC8F2SXo60NUY4/rUfUtjjDmFsxS/VbzzklhG0wWnnDYD4Tj7zj1ijInBmR1ehbOfeb3L4cE4A9plOA9irvwE5CJjt7QksAxnKXOVMeYYcAlYZpd/uwLTrLbVQAW7NSWlegyAMWY0jrapwDF8qzklPTFAP5ztCJuA9caYH1PJ6yUgm6Tx5Wq7tNwL+FlEluNoP2sPDwHqich6nO0VB2z8z0AWe43fxrnOrswAVhhjzuCZ9JZfLDARZzn/B9wHmFOAT8X9hVBPvI2zj3Wz7ZtSemGsPs6K3wacd3A+dD3o7bbumj/wEPAVsMr2nd+Q/geDNcAcnGv5tjHmSEb6m05SqjcTcMrlS+N8IWoAzsu5m3HuL6Eec0uZ5TjteCPOux/rMsR77zAKeE6cT54GymdKPbbPdKTvBnwszguhF13i2wFb7fiiApCwIrUd6GLLOz8wLpU+uwPQ3cZvw3nPAuBF4HkRWYvzIKj4Cf0fQhUlQBHnCwQfGGMeSNU4k3CrahaRXMaY83ZW+WMgyhjzQWrpbpDfbJzrsCjDnFTSjd3+c94YM8rfvvgKcbZYVjfGvOBvX5TUsSt2s40x9/rZFSUD0ZlzRQlAROQNnJcVPe0bzZTc4pp72NmsbTgzTuNTsfeIOP+Bzi7gog7MFUVR/p7ozLmiKIqiKIqiBAg6c64oiqIoiqIoAYIOzhVFURRFURQlQNDBuaIoiqIoiqIECDo4VxRFURRFUZQAQQfniqIoiqIoihIg6OBcURRFURRFUQKE/wcTo0aoGRo12wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd8f9d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(13, 9))\n",
    "sns.heatmap(data_corr,annot=True)\n",
    "\n",
    "# Mask unimportant features\n",
    "sns.heatmap(data_corr, mask=data_corr < 1, cbar=False)\n",
    "\n",
    "plt.savefig('cnt.png' )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
